Relevant bibliographies by topics / Personalized medicin

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Personalized medicin'

Author: Grafiati
Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "Personalized medicin"

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Pereginya, O. V. ,. "TRANSLATION MEDICINE, BIOMEDICINE AND MEDICAL BIOTECHNOLOGY: THE TRANSITION TO PERSONALIZED MEDICINE." Biotechnologia Acta 13, no. 2 (April 2020): 5–11. http://dx.doi.org/10.15407/biotech13.02.005.

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Teixeira, Túlio Weslley Dantas, Maria Carolina Wanderley, and Roberta Luciana do Nascimento Godone. "Medicina personalizada no tratamento do câncer/Personalized medicine in cancer treatment." Brazilian Journal of Health Review 3, no. 6 (2020): 18789–93. http://dx.doi.org/10.34119/bjhrv3n6-266.

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Teixeira, Túlio Weslley Dantas, Maria Carolina Wanderley, and Roberta Luciana do Nascimento Godone. "Medicina personalizada no tratamento do câncer/Personalized medicine in cancer treatment." Brazilian Journal of Health Review 3, no. 6 (2020): 18789–93. http://dx.doi.org/10.34119/bjhrv3n6-266.

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Kutty, Dr AVM. "Personalized Medicine : An Overview." JOURNAL OF CLINICAL AND BIOMEDICAL SCIENCES 08, no. 2 (June 15, 2018): 36–38. http://dx.doi.org/10.58739/jcbs/v08i2.7.

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The advancements in Science and Technology are paving way to reconsider the manner in which we define disease, drug development, diagnosis and treatment. The analytical capabilities of biological specimens have seen an explosion and have contributed tremendously to the diagnosis of diseases in general and genetic diseases in particular. There is a transformation of description of diseases from simple anatomical location and clinical symptoms which failed to take into consideration the unique biological profile of the patient, which could determine the therapeutic efficacy of the drugs being administered.
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Awwalu, Jamilu, Ali Garba Garba, Anahita Ghazvini, and Rose Atuah. "Artificial Intelligence in Personalized Medicine Application of AI Algorithms in Solving Personalized Medicine Problems." International Journal of Computer Theory and Engineering 7, no. 6 (December 2015): 439–43. http://dx.doi.org/10.7763/ijcte.2015.v7.999.

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P, Ajmal Rasi K., and Puneeth Vishnukeerthy K. "Personalized Medicine Revolution Medicine based on Genomics Makeup." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (June 30, 2018): 433–39. http://dx.doi.org/10.31142/ijtsrd12982.

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Singhal, Dr Udita. "Personalized Medicine: Evolving paradigm in Pathology." Recent Advances in Pathology & Laboratory Medicine 3, no. 2 (August 21, 2017): 17–22. http://dx.doi.org/10.24321/2454.8642.201703.

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Movafagh, Abolfazl. "Personalised Medicine in Modern Era." Asian Pacific Journal of Cancer Biology 1, no. 2 (June 25, 2016): 31–32. http://dx.doi.org/10.31557/apjcb.2016.1.2.31-32.

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Personalised Medicine is a medical procedure that separates patients into different groups-with medical decisions, practices, interventions and/or products being tailored to the individual patient based on their predicted response or risk of disease. The terms personalized medicine, precision medicine, stratified medicine are used interchangeably to describe this concept.
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Suhonen, Riitta, Minna Stolt, and David Edvardsson. "Personalized Nursing and Health Care: Advancing Positive Patient Outcomes in Complex and Multilevel Care Environments." Journal of Personalized Medicine 12, no. 11 (November 1, 2022): 1801. http://dx.doi.org/10.3390/jpm12111801.

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Nardini, Christine, Venet Osmani, Paola G. Cormio, Andrea Frosini, Mauro Turrini, Christos Lionis, Thomas Neumuth, Wolfgang Ballensiefen, Elio Borgonovi, and Gianni D’Errico. "The evolution of personalized healthcare and the pivotal role of European regions in its implementation." Personalized Medicine 18, no. 3 (May 2021): 283–94. http://dx.doi.org/10.2217/pme-2020-0115.

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Personalized medicine (PM) moves at the same pace of data and technology and calls for important changes in healthcare. New players are participating, providing impulse to PM. We review the conceptual foundations for PM and personalized healthcare and their evolution through scientific publications where a clear definition and the features of the different formulations are identifiable. We then examined PM policy documents of the International Consortium for Personalised Medicine and related initiatives to understand how PM stakeholders have been changing. Regional authorities and stakeholders have joined the race to deliver personalized care and are driving toward what could be termed as the next personalized healthcare. Their role as a key stakeholder in PM is expected to be pivotal.
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Dissertations / Theses on the topic "Personalized medicin"

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BHARAT, ROHIT. "Targeting cancer cell metabolism: Gateway towards personalized medicine." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2019. http://hdl.handle.net/10281/241161.

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Nell'ultimo decennio, uno dei messaggi chiave derivante dalle ricerche scientifiche sul cancro è la necessità di comprendere meglio il metabolismo delle cellule tumorali per lo sviluppo di una terapia personalizzata migliore e più efficace. Le cellule tumorali attuano un riarrangiamento metabolico che coinvolge diversi processi per supportare la loro natura proliferativa ed invasiva. Per meglio comprendere l’entità del cambiamento metabolico, in questo studio abbiamo utilizzato un approccio systems level impiegando la metabolomica untargeted e la flussomica mediante isotopi stabili del carbonio (13C) in cellule tumorali esprimenti un K-Ras oncogenico. Abbiamo testato gli effetti di farmaci inibitori del metabolismo di glucosio e glutammina per indagare eventuali vie metaboliche alternative attivate per la sopravvivenza delle cellule tumorali. Inoltre abbiamo investigato il ruolo del metabolismo cellulare nello sviluppo della resistenza alla terapia endocrina nel carcinoma mammario ERα positivo. I dati ottenuti hanno permesso di identificare specifici meccanismi metabolici di utilizzo della glutammina in cellule resistenti alla terapia, suggerendo l’utilizzo del farmaco metformina come adiuvante nel trattamento dei tumori resistenti alla terapia ormonale. Infine, abbiamo contribuito alla comprensione del metabolismo delle cellule tumorali nel guidare la crescita e la proliferazione, esplorando il ruolo della glutammina oltre la nota funzione di fonte di carbonio e azoto; infatti sostituendo la glutammina con fonti alternative di carbonio e azoto, si osserva un fenotipo reverse Warburg. I risultati di questa tesi aprono strade di ricerca per l'identificazione di nuovi potenziali obiettivi terapeutici e ci portano verso la progettazione di una strategia terapeutica migliore e più efficace per il trattamento dei pazienti oncologici.
In the recent decade, one of the important keynote message derived through the summation of our global efforts against cancer is the need to better understand cancer cell metabolism for the development of better and efficacious personalized therapy. Cancer cells undertake a multifaceted rewiring of metabolic pathways in order to support their proliferative and invasive nature, which requires a systems level investigation to fully comprehend the scale of metabolic deregulation. In this study, we systematically investigated the metabolic differences using untargeted metabolomics and 13C flux omics approach in oncogenic K-Ras driven tumours. We tested the effects of drug inhibitors targeting glucose and glutamine metabolism to unravel the alternative metabolic pathways required for cancer cell survival. We further expanded our research towards understanding the role of cellular metabolism in driving resistance to endocrine therapeutic drugs in ERα positive breast cancer. We identified specific metabolic mechanisms of utilization of glutamine in resistant cells while also providing further basis for the use of metformin as an adjuvant in the treatment of endocrine therapyresistant cancers. Finally, we contributed to current understanding about cancer cell metabolism by exploring the role of glutamine beyond its role as a carbon and nitrogen source in driving growth and proliferation of cancer cells. Upon substitution of glutamine with appropriateiv nitrogen and carbon sources, cancer cells exhibited reverse Warburg phenotype. The findings from this thesis open up new avenues of research through the identification of new putative targets and bring us one step closer towards designing much better and efficacious therapeutic strategy for the treatment of cancer patients.
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Götze, Sarah, Daniella Ekström, Forssén Tore Larsson, Eric Sjöö, Frisinger Emma Svanberg, and Linnea Wikström. "Personalized Medicine." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-444200.

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The aim of this project was to present several therapies and possible applications of these in the field of personalized medicine along with the production techniques and workflows surrounding them. There are two main categories; cell therapies and non-cell therapies. Cell therapies utilize the body's own T cells and immune system, and non-cell therapies are mostly based on proteins and nucleotides. All of these applications face different challenges that need to be overcome to be considered effective treatments and they all have a high production cost. The report also presents differences and similarities of manufacturing models that are specifically used in the production of cell therapies. It could be argued that these manufacturing models can be adjusted and work for both cell therapies and non-cell therapies. Three different workflows for three different personalized medicines, antibody drug conjugates (ADCs), tumor infiltrating lymphocytes (TILs) and mRNA vaccines, are presented in this report. Technologies and processes valuable to the manufacturing process were also presented, including bioreactors, interleukin 2 media and cell dissociation technologies. In conclusion, there are methods and techniques that are frequently used in production that are, or possibly could be useful for manufacturing personalized drug components. Production of products used in personalized medicine is possible if the right resources are available. Personalized therapies are presently most commonly applied to cancer diseases but there are developments for these therapies that could benefit several other diseases. To fully apply personalized therapies to these diseases further studies on suitable biomarkers and targets in drugs are needed. Overall, personalized medicine has promising possibilities in treatments for many types of complex diseases. This project was assigned by Cytiva which is a global life science company and the product order can be seen in the appendix.
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Marín, Falco Matías. "Estudio de la heterogeneidad regulatoria en cáncer y sus implicaciones en la medicina personalizada." Doctoral thesis, Universitat Politècnica de València, 2021. http://hdl.handle.net/10251/165413.

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[ES] El cáncer es la segunda causa de muerte en el mundo y se caracteriza principalmente por la proliferación descontrolada de las células que forman el tumor. Aunque el desarrollo de un tumor es posible debido a ciertos procesos comunes desencadenados por la desregulación del equilibrio existente entre los componentes moleculares de una célula y sus elementos de control, existe una gran heterogeneidad en los mecanismos a través de los cuales ocurre dicha desregulación. Gracias al desarrollo de nuevas tecnologías de secuenciación ha sido posible observar como esta heterogeneidad no solo se observa entre los distintos tipos de tumores sino entre las propias células de un mismo tumor. La caracterización de la heterogeneidad tumoral ha tenido un gran impacto en la comprensión de la enfermedad y el desarrollo de nuevas terapias dirigidas. Por este motivo, con el fin de mejorar la caracterización de alteraciones en los distintos mecanismos regulatorios, en esta tesis se han desarrollado dos metodologías con gran potencial para su aplicación en la medicina personalizada y que permiten estudiar la heterogeneidad inter e intratumoral de los estados de activación de elementos reguladores. En primer lugar, se desarrolló una metodología que permite determinar en una muestra el estado de activación de los factores de transcripción (FTs) a partir de la expresión de los genes a los que regula. Se aplicó la metodología para realizar un análisis sistemático de varios cánceres (conocido como estudios pan-cáncer) en el que se caracterizó por primera vez el escenario regulatorio de 52 FTs en 11 tipos de cáncer distintos. Además, al poder obtener valores de activación individuales para cada muestra, fue posible observar correlaciones entre la activación de algunos FTs con la supervivencia, sugiriendo así su uso como marcadores pronósticos. En segundo lugar, se desarrolló otra metodología en la que se emplea un modelo mecanístico para determinar el estado de activación de alrededor de 1000 circuitos de señalización a partir de datos de experimentos transcriptómicos de células únicas (scRNAseq). El uso de este modelo mecanístico en datos de scRNAseq de 4 pacientes de glioblastoma, además de mostrar la heterogeneidad intratumoral presente en las muestras, ha permitido realizar intervenciones in silico para simular el efecto de distintas drogas sobre las células. De esta manera, ha sido posible describir posibles mecanismos mediante los cuales un grupo de células pueden evitar el efecto de una terapia dirigida. Las metodologías desarrolladas en esta tesis, así como los resultados obtenidos tras su aplicación supone una valiosa fuente de información para el desarrollo de marcadores de diagnóstico, pronóstico y respuesta que ayuden a entender mejor los distintos niveles de heterogeneidad presentes en cáncer, y así, poder aumentar la eficacia de las terapias dirigidas.
[CA] El càncer és la segona causa de mort al món i es caracteritza principalment per la proliferació descontrolada de les cèl·lules que formen el tumor. Encara que el desenvolupament d'un tumor és possible a causa de certs processos comuns desencadenats per la desregulació de l'equilibri existent entre els components moleculars d'una cèl·lula i els seus elements de control, hi ha una gran heterogeneïtat en els mecanismes a través dels quals s'aconseguix aquesta desregulació. Gràcies a el desenvolupament de noves tecnologies de seqüenciació ha sigut possible observar com aquesta heterogeneïtat no només s'observa entre els diferents tipus de tumors sinó entre les pròpies cèl·lules d'un mateix tumor. La caracterització de l'heterogeneïtat tumoral ha tingut un gran impacte en la comprensió de la malaltia i el desenvolupament de noves teràpies dirigides. Per aquest motiu, per tal de millorar la caracterització d'alteracions en els diferents mecanismes reguladors, en aquesta tesi s'han desenvolupat dues metodologies amb gran potencial per a la seua aplicació en la medicina personalitzada i que permeten estudiar l'heterogeneïtat inter i intratumoral dels estats de activació d'elements reguladors. En primer lloc es va desenvolupar una metodologia que permet determinar en una mostra l'estat d'activació dels factors de transcripció (FTs) a partir de l'expressió dels gens als que regula. Es va aplicar la metodologia per a realitzar una anàlisi de pan-cancer en el qual es va caracteritzar per primera vegada l'escenari regulatori de 52 FTs a 11 tipus de càncer diferents. A més, al poder obtenir valors d'activació individuals per a cada mostra, va ser possible observar correlacions entre l'activació d'alguns FTs amb la supervivència, suggerint així el seu ús com a marcadors pronòstics. En segon lloc, es va desenvolupar una altra metodologia en la qual s'empra un model mecanístic per determinar l'estat d'activació d'al voltant de 1000 circuits de senyalització a partir d'experiments transcriptòmics de cèl·lules úniques (scRNAseq). L'ús d'aquest model mecanístic en dades de scRNAseq de 4 pacients de glioblastoma, a més de mostrar l'heterogeneïtat intratumoral present en les mostres, ha permès realitzar intervencions in silico per simular l'efecte de diferents drogues sobre les cèl·lules. D'aquesta manera, ha estat possible descriure possibles mecanismes mitjançant els quals un grup de cèl·lules poden evitar l'efecte d'una teràpia dirigida. Les metodologies desenvolupades en aquesta tesi, així com els resultats obtinguts després de la seva aplicació suposa una valuosa font d'informació per al desenvolupament de marcadors de diagnòstic, pronòstic i resposta que ajudin a entendre millor els diferents nivells d'heterogeneïtat presents en càncer, i així, poder augmentar l'eficàcia de les teràpies dirigides.
[EN] Cancer is the second leading cause of death in the world and is characterized mainly by the uncontrolled proliferation of the cells that make up the tumor. Although the development of a tumor is possible due to certain common processes triggered by the dysregulation of the existing balance between the molecular components of a cell and its control elements, there is great heterogeneity in the mechanisms through which this dysregulation is achieved. Thanks to the development of new sequencing technologies, it has been possible to observe how this heterogeneity is not only observed between the different types of tumors but also between the cells of the same tumor. The characterization of tumor heterogeneity has had a great impact on the understanding of the disease and the development of new targeted therapies. For this reason, in order to improve the characterization of alterations in the different regulatory mechanisms, in this thesis two methodologies have been developed that allow studying the inter- and intratumoral heterogeneity of the activation states of regulatory elements and with great potential for their application in personalized medicine. In the first place, a methodology that allows determining in a sample the activation state of the transcription factors (FTs) from the expression of the genes that it regulates was developed. The methodology was applied to perform a pan-cancer analysis in which the regulatory scenario of 52 FTs was characterized for the first time in 11 different types of cancer. Furthermore, by being able to obtain individual activation values for each sample, it was possible to observe correlations between the activation of some FTs with survival, thus suggesting their use as prognostic markers. Second, another methodology was developed using a mechanistic model to determine the activation state of around 1000 signaling circuits in single cell transcriptomic experiments (scRNAseq). The use of this mechanistic model in scRNAseq data from 4 glioblastoma patients, in addition to showing the intratumoral heterogeneity present in the samples, has allowed in silico interventions to simulate the effect of different drugs on cells. In this way, it has been possible to describe possible mechanisms by which a group of cells can avoid the effect of a targeted therapy. The methodologies developed in this thesis, as well as the results obtained after its application, is a valuable source of information for the development of diagnostic, prognostic and response markers that help to better understand the different levels of heterogeneity present in cancer, and thus, be able increase the effectiveness of targeted therapies.
Marín Falco, M. (2021). Estudio de la heterogeneidad regulatoria en cáncer y sus implicaciones en la medicina personalizada [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/165413
TESIS
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Frunza, Oana Magdalena. "Personalized Medicine through Automatic Extraction of Information from Medical Texts." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/22724.

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The wealth of medical-related information available today gives rise to a multidimensional source of knowledge. Research discoveries published in prestigious venues, electronic-health records data, discharge summaries, clinical notes, etc., all represent important medical information that can assist in the medical decision-making process. The challenge that comes with accessing and using such vast and diverse sources of data stands in the ability to distil and extract reliable and relevant information. Computer-based tools that use natural language processing and machine learning techniques have proven to help address such challenges. This current work proposes automatic reliable solutions for solving tasks that can help achieve a personalized-medicine, a medical practice that brings together general medical knowledge and case-specific medical information. Phenotypic medical observations, along with data coming from test results, are not enough when assessing and treating a medical case. Genetic, life-style, background and environmental data also need to be taken into account in the medical decision process. This thesis’s goal is to prove that natural language processing and machine learning techniques represent reliable solutions for solving important medical-related problems. From the numerous research problems that need to be answered when implementing personalized medicine, the scope of this thesis is restricted to four, as follows: 1. Automatic identification of obesity-related diseases by using only textual clinical data; 2. Automatic identification of relevant abstracts of published research to be used for building systematic reviews; 3. Automatic identification of gene functions based on textual data of published medical abstracts; 4. Automatic identification and classification of important medical relations between medical concepts in clinical and technical data. This thesis investigation on finding automatic solutions for achieving a personalized medicine through information identification and extraction focused on individual specific problems that can be later linked in a puzzle-building manner. A diverse representation technique that follows a divide-and-conquer methodological approach shows to be the most reliable solution for building automatic models that solve the above mentioned tasks. The methodologies that I propose are supported by in-depth research experiments and thorough discussions and conclusions.
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Trincado, Alonso Juan Luis 1987. "Characterization of clinically relevant RNA alterations for personalized cancer medicine." Doctoral thesis, Universitat Pompeu Fabra, 2019. http://hdl.handle.net/10803/665991.

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The following thesis tries to answer the question of wheter RNA processing alterations are informative for the clinical management of cancer patients. For this, the work is focused on solve two main issues: the development of computational tools to study RNA profiles from multiple tumors and the identification of RNA-related signatures that may be predictive of prognosis and therapy. The thesis is divided in three chapters: First, the development a new tool for fast quantification of differential splicing: SUPPA2. Second, a new methodology for elucidating the prognostic potential of alternative transcript isoforms across human tumours. And third, a new method for the detection of aberrant tumor splicing junctions and their antigenic evaluation.
La presente tesis intenta arrojar luz sobre la pregunta de si las alteraciones del ARN son informativas para el tratamiento clínico de pacientes con cancer. Para ello, este trabajo se centra en resolver dos cuestiones principales: el desarrollo de metodos computaciones para el estudio de perfiles de ARN en multiples tumores y la identificación de marcadores que puedan ser predictivos de prognosis y terapia. La tesis está dividida en tres capítulos: Primero, el desarollo de un nuevo método para la cuantificación rápida de splicing diferencial: SUPPA2. Segundo, una nueva metodologia para dilucidar el potencial prognóstico de tránscritos alternativos en tumores humanos. Y tercero, un nuevo método para la detección de junctions aberrantes tumorales y su evaluacion antigénica
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Bachur, Catherine. "Integrating social context into personalized medicine." Master's thesis, Temple University Libraries, 2019. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/549613.

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Urban Bioethics
M.A.
Personalized medicine is the idea that every patient can be treated in a unique manner, tailored specifically to his or her individual needs. Traditionally the field of personalized medicine has focused on using genetic information to determine medical treatment. However, humans are not only the sum of their genetic parts. All people exist within the context of their environment, their experiences, and their relationships. While the connection between this greater context and medical treatment may not be immediately obvious, it exists. If we are to truly tailor medical care, it must occur in a holistic manner, combining both genetics and social context. A thorough understanding of the way that they interact, as well as the individual limitations of both, is the best way to offer individualized care to all patients.
Temple University--Theses
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Papke, Todd Alan. "Personalized audio warning alerts in medicine." Diss., University of Iowa, 2014. https://ir.uiowa.edu/etd/1378.

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Modern Electronic Health Record (EHR) systems are now integral to healthcare. Having evolved from hospital billing and laboratory systems in the 80's, EHR systems have grown considerably as we learn to represent more and more aspects of patient encounter, diagnosis and treatment digitally. EHR user interfaces, however, lag considerably behind their consumer-electronics counterparts in usability, most notably with respect to customizability. This limitation is especially evident in the implementation of audible alerts that are coupled to sensors or timing devices in intensive-care settings. The most current standard, (ISO/IEC 60601-1-8) has been designed for alerts that are intended to signal situations of varying priorities: however, it is not universally implemented, and has been criticized for the difficulty that healthcare providers have in discriminating between individual alarms, and for the failure to incorporate prior research with respect to "sense of urgency" as it applies to alarm efficacy. In the present work, however, we consider that there are more effective means to allow a user to identify an alarm correctly than "sense of urgency" response. This thesis focuses on the problem of correct identification of alerts: what happens when a human subject is allowed to create or designate (i.e., personalize) one's own alerts? Given the ubiquity, low costs and commoditization of consumer-electronics devices, we believe that it is just a matter of time before such devices become the norm in critical care and replace existing, special-purpose devices for information delivery at the point of patient care. We built a tool, PASA (Personalized Alert Study Application), that would allow us to capture and edit sounds and orchestrate studies that would contrast any two types of sounds. PASA facilitated a study where study participant's responses to "personalized" sounds were contrasted with sounds that meet the ISO/IEC 60601-1-8:2012 standard. We performed two sub-studies that contrasted responses to two banks of 6-alerts and 10-alerts. The 6-alert study was repeated with the same subjects after two weeks without training to measure recall. We observed that accuracy, reaction time, and retention were significantly improved with the personalized sounds. For example, the median errors for the 6-alert baseline study were 4 for personalized vs. 27 for standard alerts. For the 6-alert repeat study it was 7 vs. 43. The median for the 10-alert study was 1 for personalized vs. 55 for standard alerts. Accuracy for recognition, while remaining constant for personalized alerts, degraded considerably for standardized alerts as the number of alerts increased from 6 to 10. We conclude that personalization of alerts may improve information delivery and reduce cognitive overload on the health care provider. This potential positive effect at the point of patient care merits further studies in a clinical or simulated clinical setting.
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Ahmed, Abdul-Kareem H. "SIGN HERE : informed consent in personalized medicine." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/83832.

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Thesis (S.M. in Science Writing)--Massachusetts Institute of Technology, Dept. of Comparative Media Studies, 2013.
Vita. Cataloged from PDF version of thesis.
Includes bibliographical references (pages 27-30).
The next era of medicine will be one of personalization, scientists and physicians promise. Personalized medicine is a refined clinical approach in which clinicians will utilize your genomic information to help you prevent disease, and tailor targeted therapies for you when you fall ill. This is the future science has slowly been approaching. However, the human genome is not enough, not unless we can decipher its language. One ambitious study to this effect is the Personal Genome Project, led by Dr. George Church at Harvard Medical School. This project will eventually recruit 100,000 volunteers to donate their genomes and a full body of information concerning their biological health. With this data, Church hopes others can cross-analyze these profiles and better determine the role in disease of each gene of the human genome. However, the Personal Genome Project is as much a study in the ethical, legal and social aspects of genomic studies as it is an effort toward personalized medicine. Church envisions a future where privacy cannot be guaranteed. Society is becoming more open and technology is more invasive than ever. Considering this, Church has informed his participants that their information will likely not remain anonymous. With their fully informed consent, he has in turn made all this data public, to promote open science. This ethical approach raises several important questions about expansive genomic studies. The scientific community will have to decide on an approach that will eventually deliver personalized medicine. On one end of the spectrum, there is Church's open approach, and the other, more security, more firewalls and more legislation. In order for personalized medicine to become a reality, society will have to prepare itself for our ever-changing ethical, technological and scientific landscape.
by Abdul-Kareem H. Ahmed.
S.M.in Science Writing
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Ceccato, Filippo. "Personalized medical treatment for pituitary adenoma." Doctoral thesis, Università degli studi di Padova, 2019. http://hdl.handle.net/11577/3421850.

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Introduction and Aim: Pituitary adenomas are common neoplasms, with a reported prevalence of about one case in 1000 subjects. Patients with pituitary adenomas show significant morbidity due to pituitary hormone hypersecretion or deficiencies, mass effects and infiltration of the surrounding tissues. Although trans-sphenoidal surgery and radiotherapy are largely used to treat patients with pituitary adenomas, the overall long-term remission rate is not complete, beside side effects of surgery or brain irradiation. Therefore, medical treatments with pituitary-directed drugs are increasingly used in patients with secreting pituitary adenomas, especially when surgery fails or is not indicated, or awaiting for effects of radiotherapy. Somatostatin analogues (SSA) have been the mainstay of the medical treatment of GH-secreting adenomas, and nowadays are also used to treat ACTH-secreting pituitary adenomas, since these tumours express several types of somatostatin receptors (SSTR), with the prevalence of SSTR type 2 in the GH-secreting PA and of SSTR type 5 in the ACTH-secreting. Regrettably, 50% of patients with GH- secreting and 60% with ACTH- secreting pituitary adenomas do not respond to medical treatment with pituitary-directed drugs, or present only a partial hormonal reduction. Receptor desensitization, internalization and intra-cellular trafficking of SSTR could explain at least partially the lack of response, hence more data and knowledge about these cellular processes are urgently needed. Moreover, pituitary adenomas are not always benignant: some aggressive cases (up to 15-20% in all series) are characterized by rapid regrowth after first surgery, invasion of the surrounding structure, resistance to medical therapy, therefore the term Pituitary Neuroendocrine Tumor (PitNET) should be actually used. The aims of this PhD project are to describe the role of medical treatment in patients with PitNET, in order to study the efficacy of available compounds; applicate the combination of medical treatment in clinical practice; analyse the differential effects (if existing) of medical treatment compared to surgery (considered the best curative treatment). Materials and methods: Among our cohort of patients (120 with GH-, 134 with ACTH-, 171 with PRL-, 6 with TSH- secreting PitNET, 150 with non-secreting PitNET), we retrospectively and prospectively analysed clinical, radiological and pathological features of patient. Considering the treatment of aggressive PitNET or patients with Cushing’s Syndrome, we focused our attention to everolimus, temozolomide (TMZ) and metyrapone (MET) treatment. In some case, primary cell culture were used to study the effect of medical treatment. Results: Regarding medical treatment, we considered the use of everolimus, TMZ, cabergoline and MET. 1. In a patient with tuberous sclerosis complex (TSC) and silent gonadotroph PitNET we tested the efficacy of everolimus, observing a reduction of cell viability after an in vitro treatment of PitNET’s derived primary cells. TSC analysis retrieved no disease-associated variants with the exception of the heterozygous intronic variant c.4006-71C>T found in TSC2: the computational tools predicted a gain of a new splice site with consequent intron retention, not confirmed by an in-vitro analysis of patient’s lymphocyte derived RNA. 2. Regarding TMZ in aggressive PitNET, we conducted an Italian survey on 31 patients: 11 patients (35.5%) had reduction of the tumor during TMZ treatment, while 6 patients (19.4%) had progression of disease. Median follow-up after start of TMZ was 18 months. Seven patients presented disease progression. The 2-yr recurrence-free survival was 62% (95% C.I., 34 -99%). Seven patients died of progressive disease. The 2-yr and 4-yr survival rates were 90% (95% C.I., 77-100%) and 56% (95% C.I., 26-85%). Moreover, we treated a patient with a combined cabergoline+TMZ treatment, achieving excellent results. 3. Considering MET in patients with Cushing’s Syndrome, patients were treated with a median dose of 1000 mg for 9 months. UFC and LNSC decreased quickly after the first month of treatment (-67% and -57% from baseline), with sustained UFC normalization up to 12 and 24 months (in 13 and 6 patients, respectively). UFC and LNSC normalized later (after 3-6 months) in patients with severe hypercortisolism (>5-fold baseline UFC). Regarding last visit, 70% and 37% of patients normalized UFC and LNSC, respectively. Body weight reduction (-4kg) was observed after UFC normalization. Severe side-effects were not reported, half female patients complained hirsutism, and blood pressure was not increased. 4. In patients with acromegaly, a significant proportion of patients developed Central Adrenal Insufficiency (CA) over time: while primary or secondary medical treatment did not contribute to the risk of CAI, repeated surgery or radiotherapy affected pituitary-adrenal axis. CAI was diagnosed in 18% of patients (10/57) after surgery, and in 53% (9/17) after radiotherapy (p=0.01). Considering those aspects related to predict the effects of medical treatment with SSA in acromegaly, we studied the role of AIP-AHR and GIPR pathway. Considering AIP-AHR axis, involved in the detoxification of endocrine disruptors and chemical pollutants, we observed that acromegaly is more biochemically severe and resistant to SSA treatment in patients living in highly polluted areas, especially if they also carry specific AHR and/or AIP gene variants. Moreover, we found a stimulatory effect of IGF-1 on GIP promoter support in GIPR-expressing somatotropinomas, suggesting a novel molecular pathway able to induce GH-secreting PitNET. Conclusions: In this complex scenario, understanding the physio-pathology of PitNET is the beginning of personalized treatment. In clinical practice, a multidisciplinary team for the management of patients is fundamental, to suggest the correct treatment plan, tailored to the patient.
Introduzione e scopo: Gli adenomi ipofisari sono neoplasie frequenti, con una prevalenza di un caso ogni 1000 soggetti. I pazienti con adenoma ipofisario possono presentare segni e sintomi in correlazione alla secrezione autonoma (o deficitaria) di ormoni ipofisari, oppure possono presentarsi come “effetto massa” dovuto alla lesione occupante spazio in loggia ipofisaria. Sebbene la chirurgia e la radioterapia siano state molto utilizzate in passato, il controllo a lungo termine non è completo, sia in termini di secrezione che di lesione adenomatosa, esponendo comunque il paziente agli effetti collaterali dell’intervento o dell’irradiazione. Pertanto, la terapia medica è sempre più utilizzata, non solo nelle recidive post-chirurgiche, ma anche quando ulteriori interventi sono inefficaci, o in attesa degli effetti della radioterapia. Gli analoghi della somatostatina (SSA) sono stati per anni la principale terapia degli adenoma GH-secernenti, e al giorno d’oggi vengono utilizzati anche in quelli ACTH-secernenti, dato il loro effetto differenziale sui recettori della somatostatina (SSTR), soprattutto il tipo 2 nei GH-secernenti e il tipo 5 negli ACTH-secernenti. Purtroppo, fino al 50% dei pazienti non risponde in maniera soddisfacente alle terapie mediche, pertanto una maggior conoscenza della biologia cellulare ipofisaria è necessaria, per capire quale sia la strategia migliore per il paziente. Inoltre, in alcuni casi gli adenomi non sono sempre benigni (circa il 15-20% delle principali serie descritte in letteratura), caratterizzandosi per la resistenza alle terapie convenzionali, l’invasione dei tessuti locali o la rapida crescita. In tali casi, il termine Tumore Neuroendocrino Ipofisario (PitNET) viene recentemente proposto in letteratura. Lo scopo di questa tesi di dottorato è di studiare gli effetti delle terapie mediche in pazienti con PitNET; per sviluppare nuove strategie terapeutiche, per capire l’efficacia dei farmaci disponibili e per testare la loro combinazione. Materiali e metodi: I pazienti che sono seguiti presso l’ambulatorio ipofisi dell’Unità Operativa di Endocrinologia dell’Azienda Ospedaliero-Universitaria di Padova (120 con PitNET GH-secernenti, 134 ACTH-secernenti, 171 PRL-secernenti, 6 TSH- secernenti e 150 PitNET non funzionanti) sono stati seguiti in uno studio retrospettivo e prospettico. I dati clinici, bioumorali, di terapia, radiologici e patologici sono stati raccolti e analizzati. Tra le varie terapie mediche, maggior risalto è stato dato all’everolimus e alla temozolomide (TMZ) nei PitNET aggressivi e al metirapone (MET) in pazienti con Sindrome di Cushing. In casi selezionati sono state allestite linee cellulari derivanti dall’adenoma del pazienti (primarie). Risultati: in termini di terapia medica abbiamo analizzato 1. In un paziente con sclerosi tuberosa e PitNET silente abbiamo testato l’efficacia dell’everolimus in colture primarie, osservando una generale riduzione della vitalità cellulare. Abbiamo poi riscontrato una nuova variante del gene TSC2, gli studi in silico predicono la ritenzione di un introne con perdita di un sito di splicing, che andrà confermato in ulteriori studi funzionali. 2. Considerando la terapia con TMZ in PitNET aggressivi abbiamo raccolto i dati di 31 pazienti provenienti da uno studio multicentrico italiano. 11 casi hanno presentato una riduzione del PitNET, con una mediana di terapia di 18 mesi. Il 90% e il 60% dei pazienti erano liberi da malattia a 2 e 4 anni dalla terapia con TMZ. Abbiamo poi trattato un paziente con TMZ e cabergolina, ottenendo ottimi risultati. 3. 31 pazienti con Sindrome di Cushing sono stati trattati per 9 mesi con 1000 mg di MET. I parametri ormonali (cortisoluria e cortisolo salivare notturno) si sono ridotti rapidamente già dopo un solo mese di terapia, normalizzando la secrezione di cortisolo fino a 12 e 24 mesi. I pazienti con ipercorticismo severo (>5 volte i valori normali al baseline) hanno raggiunto il controllo biochimico di malattia più lentamente, tuttavia il 70% dei pazienti normalizzava la cortisoluria all’ultima visita, con una riduzione media di peso di 4kg. In generale il MET era ben tollerato, senza importanti effetti collaterali. 4. Nei pazienti con acromegalia, lo sviluppo di insufficienza surrenalica centrale (CAI) non è trascurabile nel follow-up. Mentre la terapia medica non aumenta il rischio di CAI, il 18% dei pazienti (10/57) svilippa iposurrenalismo dopo la chirurgia, mentre il 53% (9/17) lo sviluppa dopo la radioterapia. Analizzando in vitro gli aspetti che potrebbero predire la efficacia della terapia con SSA nei pazienti con acromegalia, abbiamo studiato i pathway molecolari di AIP-AHR e del GIPR. L’asse AIP-AHR, coinvolto nella detossificazione di varie molecole interferenti endocrine e inquinanti chimici, si trova maggiormente mutato in pazienti acromegalici con malattia più severa e con minor risposta agli SSA, soprattutto se vivono in zone molto inquinate. Abbiamo inoltre scoperto un ruolo promuovente del recettore dell’IGF-1 nel recettore del GIP, coinvolto nella tumorogenesi ipofisaria e quindi nuovo aspetto da studiare nei PitNET GH-secernenti. Conclusioni: Comprendere a fondo la fisiopatologia dei PitNET è l’inizio della personalizzazione della terapia medica, sempre più usata oggigiorno. Nella pratica clinica quotidiana, pertanto, un team multidisciplinare è fondamentale per proporre al paziente il corretto piano terapeutico, personalizzato secondo le proprie caratteristiche biologiche.
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Ayati, Marzieh. "Algorithms to Integrate Omics Data for Personalized Medicine." Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1527679638507616.

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Books on the topic "Personalized medicin"

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Bodiroga-Vukobrat, Nada, Daniel Rukavina, Krešimir Pavelić, and Gerald G. Sander, eds. Personalized Medicine. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39349-0.

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El-Khamisy, Sherif, ed. Personalised Medicine. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60733-7.

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Jain, Kewal K. Textbook of Personalized Medicine. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2553-7.

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Jain, Kewal K. Textbook of Personalized Medicine. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-62080-6.

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Jain, Kewal K. Textbook of Personalized Medicine. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-0769-1.

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Freitas, Ana T., and Arcadi Navarro, eds. Bioinformatics for Personalized Medicine. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28062-7.

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Cohen, Nadine, ed. Pharmacogenomics and Personalized Medicine. Totowa, NJ: Humana Press, 2008. http://dx.doi.org/10.1007/978-1-59745-439-1.

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Kichko, Katharina. Personalized Medicine as Innovation. Wiesbaden: Springer Fachmedien Wiesbaden, 2019. http://dx.doi.org/10.1007/978-3-658-27843-4.

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Barh, Debmalya, Dipali Dhawan, and Nirmal Kumar Ganguly, eds. Omics for Personalized Medicine. New Delhi: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1184-6.

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service), ScienceDirect (Online, ed. Genomic and personalized medicine. Amsterdam: Elsevier/Academic Press, 2009.

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Book chapters on the topic "Personalized medicin"

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Snenghi, Rossella, and Alessandro Amagliani. "Medicines and Driving Personalized Medicine and Medical Liability." In P5 Medicine and Justice, 486–99. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67092-8_32.

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Pavelić, Krešimir, Sandra Kraljević Pavelić, and Mirela Sedić. "Personalized Medicine: The Path to New Medicine." In Personalized Medicine, 1–19. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39349-0_1.

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Ayer, Turgay, and Qiushi Chen. "Personalized Medicine." In Handbook of Healthcare Analytics, 109–35. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119300977.ch6.

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Ortega, Victor E. "Personalized Medicine." In Respiratory Medicine, 149–71. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-43447-6_13.

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Bartnik, Ewa. "Personalized Medicine." In Encyclopedia of Global Bioethics, 2214–18. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-09483-0_334.

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Peissig, Peggy, Anne Nikolai, Ingrid Glurich, and Murray Brilliant. "Personalized Medicine." In Drug Discovery and Evaluation: Pharmacological Assays, 4235–49. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-05392-9_117.

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Bartnik, Ewa. "Personalized Medicine." In Encyclopedia of Global Bioethics, 1–5. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-05544-2_334-1.

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Goodsaid, Federico, Felix Frueh, and Michael E. Burczynski. "Personalized Medicine." In Drug Discovery and Evaluation: Methods in Clinical Pharmacology, 1–14. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-56637-5_47-1.

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Foster, Simmie L., Samuel R. Petrie, David Mischoulon, and Maurizio Fava. "Personalized Medicine." In The Massachusetts General Hospital Guide to Depression, 109–21. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97241-1_8.

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Goodsaid, Federico, Felix Frueh, and Michael E. Burczynski. "Personalized Medicine." In Drug Discovery and Evaluation: Methods in Clinical Pharmacology, 425–38. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-68864-0_47.

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Conference papers on the topic "Personalized medicin"

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Tarabrin, R. E., and E. S. Pyatigorec. "BIOETHICAL ISSUES OF VACCINOMICS." In I International Congress “The Latest Achievements of Medicine, Healthcare, and Health-Saving Technologies”. Kemerovo State University, 2023. http://dx.doi.org/10.21603/-i-ic-130.

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Vaccinomics, as one of the areas of personalized medicine, can increase the effectiveness of vaccines, including in epidemics. Nevertheless, it is accompanied by a cluster of bioethical issues. The article explores possible bioethical difficulties associated with the development of personalized vaccines: the matching of the research subject and the person receiving the vaccine; the problem of confidential genetic data; equitable distribution of medical resources.
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Gribova, Valeriya, Dmitriy Okun', and Roman Kovalev. "PRINCIPLES AND ARCHITECTURE OF THE SPECIALIZED SHELL FOR BUILDING INTELLIGENT SYSTEMS FOR TREATMENT PRESCRIBE." In XIV International Scientific Conference "System Analysis in Medicine". Far Eastern Scientific Center of Physiology and Pathology of Respiration, 2020. http://dx.doi.org/10.12737/conferencearticle_5fe01d9bd6c696.88986403.

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The paper describes the basic principles of development and architecture of an intelligent medical decision support system based on a specialized shell. The system allows you to prescribe a personalized treatment in various fields of medicine. The system is based on the ontological approach and uses generally accepted medical terminology to form knowledge
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Бородин, Евгений, and Evgeniy Borodin. "PERSONALIZED MEDICINE." In XII International Scientific Conference (correspondence, electronic) "System analysis in medicine" (SAM 2018). Far Eastern Scientific Center of Physiology and Pathology of Respiration, 2018. http://dx.doi.org/10.12737/conferencearticle_5bdaace39176e3.14425520.

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Kim, Jonghyeok, Hosung Kwon, Jonghyeon Kim, Jinsoo Park, Soong-Un Choi, and Sookyung Kim. "PillGood: Automated and Interactive Pill Dispenser Using Facial Recognition for Safe and Personalized Medication." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/854.

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Safety of taking medicine prescribed differently to each patient in hospital relies on the discernment of medical professionals who deals with measuring pill quantity, packaging, and distributing. It is difficult and time consuming to keep track of medication record of each patient. Also, medication safety is prone to be in risk due to the human error. To help patients get accurate medication following their prescription plan with minimizing human labors and mistakes, we developed PillGood, an automated smart pill dispenser system using facial recognition technique. PillGood provides real-time and personalized guidance to take the correct medicine by alarming patients and distributing exact quantity of pills at specific time following each patient's prescription table. The system notify patients through mobile app and speaker when they need to take the medicine, and detect who the patient is through the machine learning based face recognition. Then, based on each patient's prescribing information, the controller distributes pills to each patient. Results show that PillGood enable highly accurate personalized pill dispensation followed by precise face recognition, benefiting both patients and medical professionals. Videos for demonstrating the system can be found on https://youtu.be/Wx7bXxRGjXA
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Morozova, T. V., and L. V. Pokhodzey. "PROMISING DIRECTIONS OF SCIENTIFIC AND PEDAGOGICAL WORK OF THE DEPARTMENT OF OCCUPATIONAL MEDICINE, AVIATION, SPACE AND DIVING MEDICINE." In The 16th «OCCUPATION and HEALTH» Russian National Congress with International Participation (OHRNC-2021). FSBSI “IRIOH”, 2021. http://dx.doi.org/10.31089/978-5-6042929-2-1-2021-1-355-358.

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Abstract: The main promising directions of research activities of the department and pedagogical work with the use of new forms of professional training of specialists in the field of occupational medicine based on the concept of lifelong education and a competence-based approach are presented. The department develops "biomedicine of the future" with the involvement of the latest achievements in the field of medical biochemistry, molecular biology, bioengineering, biotechnology, medical radiobiology. The department carries out the development and implementation of programs of higher professional education for students and residents of Sechenov University and students of the DPO system, taking into account the approaches of personalized and evidence-based medicine. The department has introduced new educational technologies (blended learning), is developing modern on-line services and modular programs.
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Chen, Huiyuan, and Jing Li. "Learning Data-Driven Drug-Target-Disease Interaction via Neural Tensor Network." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/477.

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Precise medicine recommendations provide more effective treatments and cause fewer drug side effects. A key step is to understand the mechanistic relationships among drugs, targets, and diseases. Tensor-based models have the ability to explore relationships of drug-target-disease based on large amount of labeled data. However, existing tensor models fail to capture complex nonlinear dependencies among tensor data. In addition, rich medical knowledge are far less studied, which may lead to unsatisfied results. Here we propose a Neural Tensor Network (NeurTN) to assist personalized medicine treatments. NeurTN seamlessly combines tensor algebra and deep neural networks, which offers a more powerful way to capture the nonlinear relationships among drugs, targets, and diseases. To leverage medical knowledge, we augment NeurTN with geometric neural networks to capture the structural information of both drugs’ chemical structures and targets’ sequences. Extensive experiments on real-world datasets demonstrate the effectiveness of the NeurTN model.
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Ayday, Erman, Jean Louis Raisaro, Jean-Pierre Hubaux, and Jacques Rougemont. "Protecting and evaluating genomic privacy in medical tests and personalized medicine." In CCS'13: 2013 ACM SIGSAC Conference on Computer and Communications Security. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2517840.2517843.

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Kuhlmann, Joel, and Tom Halvorsen. "Precision Medicine: Integrating Medical Images, Design Tools and 3D Printing to Create Personalized Medical Solutions." In 2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA). IEEE, 2018. http://dx.doi.org/10.1109/memea.2018.8438798.

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Yeung, Ka Yee. "Signature discovery for personalized medicine." In 2013 IEEE International Conference on Intelligence and Security Informatics (ISI). IEEE, 2013. http://dx.doi.org/10.1109/isi.2013.6578854.

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De Micheli, Giovanni, Cristina Boero, Camilla Baj-Rossi, Irene Taurino, and Sandro Carrara. "Integrated biosensors for personalized medicine." In the 49th Annual Design Automation Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2228360.2228363.

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Reports on the topic "Personalized medicin"

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Howard, David, Jason Hockenberry, and Guy David. Personalized Medicine When Physicians Induce Demand. Cambridge, MA: National Bureau of Economic Research, November 2017. http://dx.doi.org/10.3386/w24054.

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Egan, Mark, and Tomas Philipson. Health Care Adherence and Personalized Medicine. Cambridge, MA: National Bureau of Economic Research, July 2014. http://dx.doi.org/10.3386/w20330.

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Pasinetti, Giulio M. Personalized Medicine in Veterans with Traumatic Brain Injuries. Fort Belvoir, VA: Defense Technical Information Center, May 2009. http://dx.doi.org/10.21236/ada505340.

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Pasinetti, Giulio M. Personalized Medicine in Veterans with Traumatic Brain Injuries. Fort Belvoir, VA: Defense Technical Information Center, May 2012. http://dx.doi.org/10.21236/ada573371.

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Pasinetti, Giulio M. Personalized Medicine in Veterans with Traumatic Brain Injuries. Fort Belvoir, VA: Defense Technical Information Center, May 2013. http://dx.doi.org/10.21236/ada584500.

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Pasinetti, Giulio M. Personalized Medicine in Veterans with Traumatic Brain Injuries. Fort Belvoir, VA: Defense Technical Information Center, May 2011. http://dx.doi.org/10.21236/ada555685.

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Manski, Charles. Credible Ecological Inference for Personalized Medicine: Formalizing Clinical Judgment. Cambridge, MA: National Bureau of Economic Research, September 2016. http://dx.doi.org/10.3386/w22643.

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Manski, Charles. Probabilistic Prediction for Binary Treatment Choice: with Focus on Personalized Medicine. Cambridge, MA: National Bureau of Economic Research, October 2021. http://dx.doi.org/10.3386/w29358.

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Hult, Kristopher. Measuring the Potential Health Impact of Personalized Medicine: Evidence from MS Treatments. Cambridge, MA: National Bureau of Economic Research, October 2017. http://dx.doi.org/10.3386/w23900.

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Enstrom, K. G., E. Lee, and C. Ye. Requirements Document for the Design and Implementation of a Personalized Medicine Machine (PMM) Based on Microencapsulation. Office of Scientific and Technical Information (OSTI), August 2019. http://dx.doi.org/10.2172/1557040.

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