Academic literature on the topic 'Entrepôt de données de santé'
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Journal articles on the topic "Entrepôt de données de santé"
Bories, M., A. Bannay, G. Bouzillé, and P. Le Corre. "Développement d'algorithmes mesurant l'exposition médicamenteuse cumulée à partir d'un entrepôt de données de santé." Journal of Epidemiology and Population Health 72 (March 2024): 202248. http://dx.doi.org/10.1016/j.jeph.2024.202248.
Full textKarunakaran, S., D. Van Gysel, S. Guinemer, I. Mahe, and K. Sallah. "Reconstruction de variables structurées à partir des données textuelles d’un entrepôt de données de santé, à des fins de recherche clinique, Paris." Revue d'Épidémiologie et de Santé Publique 68 (March 2020): S28. http://dx.doi.org/10.1016/j.respe.2020.01.061.
Full textMille, B., D. Staumont-Sallé, V. Sobanski, D. Lannoy, J. Bene, S. Azib, S. Gautier, L. Shorten, and F. Dezoteux. "Création d’une base de données concernant la prise en charge des toxidermies en milieu hospitalier entre 2010 et 2020 à partir d’un entrepôt de données de santé." Annales de Dermatologie et de Vénéréologie - FMC 3, no. 8 (December 2023): A138—A139. http://dx.doi.org/10.1016/j.fander.2023.09.177.
Full textJean, C., P. Caillet, M. Laurent, S. Bréant, P.-A. Natella, P. Boudou-Roquette, E. Paillaud, E. Audureau, and F. Canouï-Poitrine. "Caractérisation des trajectoires de soins hospitalières des patients âgés atteints de cancer: chaînage d'une cohorte clinique avec un entrepôt de données de santé." Revue d'Épidémiologie et de Santé Publique 71 (March 2023): 101499. http://dx.doi.org/10.1016/j.respe.2023.101499.
Full textPiarroux, R., F. Batteux, S. Rebaudet, and P. Y. Boelle. "Les indicateurs d’alerte et de surveillance de la Covid-19." Annales françaises de médecine d’urgence 10, no. 4-5 (September 2020): 333–39. http://dx.doi.org/10.3166/afmu-2020-0277.
Full textLamer, A., B. Popoff, B. Delange, M. Doutreligne, E. Chazard, R. Marcilly, S. Priou, and P. Quindroit. "Difficultés et barrières rencontrées avec les entrepôts de données de santé : recommandations d'une enquête auprès d'experts en réutilisation des données." Journal of Epidemiology and Population Health 72 (March 2024): 202243. http://dx.doi.org/10.1016/j.jeph.2024.202243.
Full textAzoyan, L., Y. Lombardi, J. S. Rech, J. P. Haymann, C. Wu, S. Le Jeune, L. Affo, et al. "Risque d’insuffisance rénale aiguë après injection de produit de contraste iodé chez les adultes atteints de drépanocytose : une série de cas autocontrôlés issue d’un entrepôt de données de santé multicentrique." La Revue de Médecine Interne 43 (December 2022): A353—A354. http://dx.doi.org/10.1016/j.revmed.2022.10.053.
Full textChevalier, K., M. Genin, T. Petit Jean, J. Avouac, R. M. Flipo, S. Georgin-Lavialle, S. El Mahou, et al. "AB1131 IDENTIFICATION OF FACTORS ASSOCIATED WITH THE OCCURRENCE OF SEVERE FORMS OF COVID-19 INFECTION IN PATIENTS WITH AUTOIMMUNE/INFLAMMATORY RHEUMATIC DISEASES." Annals of the Rheumatic Diseases 81, Suppl 1 (May 23, 2022): 1682.2–1683. http://dx.doi.org/10.1136/annrheumdis-2022-eular.3245.
Full textChateau, Y., R. Schiappa, J. Gal, J. Viotti, A. Bozec, M. C. Etienne-Grimaldi, O. Dassonville, D. Borchiellini, and E. Chamorey. "Entrepôt de données des essais thérapeutiques, valoriser quinze ans de données de recherche clinique." Revue d'Épidémiologie et de Santé Publique 66 (May 2018): S133—S134. http://dx.doi.org/10.1016/j.respe.2018.03.340.
Full textVétois, Jacques. "Les données de santé." Terminal, no. 108-109 (June 1, 2011): 113. http://dx.doi.org/10.4000/terminal.1340.
Full textDissertations / Theses on the topic "Entrepôt de données de santé"
Khnaisser, Christina. "Méthode de construction d'entrepôt de données temporalisé pour un système informationnel de santé." Mémoire, Université de Sherbrooke, 2016. http://hdl.handle.net/11143/8386.
Full textKempf, Emmanuelle. "Structuration, standardisation et enrichissement par traitement automatique du langage des données relatives au cancer au sein de l’entrepôt de données de santé de l’Assistance Publique – Hôpitaux de Paris." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS694.
Full textCancer is a public health issue for which the improvement of care relies, among other levers, on the use of clinical data warehouses (CDWs). Their use involves overcoming obstacles such as the quality, standardization and structuring of the care data stored there. The objective of this thesis was to demonstrate that it is possible to address the challenges of secondary use of data from the Assistance Publique - Hôpitaux de Paris (AP-HP) CDW regarding cancer patients, and for various purposes such as monitoring the safety and quality of care, and performing observational and experimental clinical research. First, the identification of a minimal data set enabled to concentrate the effort of formalizing the items of interest specific to the discipline. From 15 identified items, 4 use cases from distinct medical perspectives were successfully developed: automation of calculations of safety and quality of care required for the international certification of health establishments , clinical epidemiology regarding the impact of public health measures during a pandemic on the delay in cancer diagnosis, decision support regarding the optimization of patient recruitment in clinical trials, development of neural networks regarding prognostication by computer vision. A second condition necessary for the CDW use in oncology is based on the optimal and interoperable formalization between several CDWs of this minimal data set. As part of the French PENELOPE initiative aiming at improving patient recruitment in clinical trials, the thesis assessed the added value of the oncology extension of the OMOP common data model. This version 5.4 of OMOP enabled to double the rate of formalization of prescreening criteria for phase I to IV clinical trials. Only 23% of these criteria could be automatically queried on the AP-HP CDW, and this, modulo a positive predictive value of less than 30%. This work suggested a novel methodology for evaluating the performance of a recruitment support system: based on the usual metrics (sensitivity, specificity, positive predictive value, negative predictive value), but also based on additional indicators characterizing the adequacy of the model chosen with the CDW related (rate of translation and execution of queries). Finally, the work showed how natural language processing related to the CDW data structuring could enrich the minimal data set, based on the baseline tumor dissemination assessment of a cancer diagnosis and on the histoprognostic characteristics of tumors. The comparison of textual extraction performance metrics and the human and technical resources necessary for the development of rules and machine learning systems made it possible to promote, for a certain number of situations, the first approach. The thesis identified that automatic rule-based preannotation before a manual annotation phase for training a machine learning model was an optimizable approach. The rules seemed to be sufficient for textual extraction tasks of a certain typology of entities that are well characterized on a lexical and semantic level. Anticipation and modeling of this typology could be possible upstream of the textual extraction phase, in order to differentiate, depending on each type of entity, to what extent machine learning should replace the rules. The thesis demonstrated that a close attention to a certain number of data science challenges allowed the efficient use of a CDW for various purposes in oncology
Lamer, Antoine. "Contribution à la prévention des risques liés à l’anesthésie par la valorisation des informations hospitalières au sein d’un entrepôt de données." Thesis, Lille 2, 2015. http://www.theses.fr/2015LIL2S021/document.
Full textIntroduction Hospital Information Systems (HIS) manage and register every day millions of data related to patient care: biological results, vital signs, drugs administrations, care process... These data are stored by operational applications provide remote access and a comprehensive picture of Electronic Health Record. These data may also be used to answer to others purposes as clinical research or public health, particularly when integrated in a data warehouse. Some studies highlighted a statistical link between the compliance of quality indicators related to anesthesia procedure and patient outcome during the hospital stay. In the University Hospital of Lille, the quality indicators, as well as the patient comorbidities during the post-operative period could be assessed with data collected by applications of the HIS. The main objective of the work is to integrate data collected by operational applications in order to realize clinical research studies.Methods First, the data quality of information registered by the operational applications is evaluated with methods … by the literature or developed in this work. Then, data quality problems highlighted by the evaluation are managed during the integration step of the ETL process. New data are computed and aggregated in order to dispose of indicators of quality of care. Finally, two studies bring out the usability of the system.Results Pertinent data from the HIS have been integrated in an anesthesia data warehouse. This system stores data about the hospital stay and interventions (drug administrations, vital signs …) since 2010. Aggregated data have been developed and used in two clinical research studies. The first study highlighted statistical link between the induction and patient outcome. The second study evaluated the compliance of quality indicators of ventilation and the impact on comorbity.Discussion The data warehouse and the cleaning and integration methods developed as part of this work allow performing statistical analysis on more than 200 000 interventions. This system can be implemented with other applications used in the CHRU of Lille but also with Anesthesia Information Management Systems used by other hospitals
Bouba, Fanta. "Système d'information décisionnel sur les interactions environnement-santé : cas de la Fièvre de la Vallée du Rift au Ferlo (Sénégal)." Thesis, Paris 6, 2015. http://www.theses.fr/2015PA066461/document.
Full textOur research is in part of the QWeCI european project (Quantifying Weather and Climate Impacts on Health in Developing Countries, EU FP7) in partnership with UCAD, the CSE and the IPD, around the theme of environmental health with the practical case on vector-borne diseases in Senegal and particularly the Valley Fever (RVF). The health of human and animal populations is often strongly influenced by the environment. Moreover, research on spread factors of vector-borne diseases such as RVF, considers this issue in its dimension both physical and socio-economic. Appeared in 1912-1913 in Kenya, RVF is a widespread viral anthropo-zoonosis in tropical regions which concerns animals but men can also be affected. In Senegal, the risk area concerns mainly the Senegal River Valley and the forestry-pastoral areas Ferlo. With a Sahelian climate, the Ferlo has several ponds that are sources of water supply for humans and livestock but also breeding sites for potential vectors of RVF. The controlling of the RVF, which is crossroads of three (03) large systems (agro-ecological, pathogen, economic/health/social), necessarily entails consideration of several parameters if one wants to first understand the mechanisms emergence but also consider the work on risk modeling. Our work focuses on the decision making process for quantify the use of health data and environmental data in the impact assessment for the monitoring of RVF. Research teams involved produce data during their investigations periods and laboratory analyzes. The growing flood of data should be stored and prepared for correlated studies with new storage techniques such as datawarehouses. About the data analysis, it is not enough to rely only on conventional techniques such as statistics. Indeed, the contribution on the issue is moving towards a predictive analysis combining both aggregate storage techniques and processing tools. Thus, to discover information, it is necessary to move towards datamining. Furthermore, the evolution of the disease is strongly linked to environmental spatio-temporal dynamics of different actors (vectors, viruses, and hosts), cause for which we rely on spatio-temporal patterns to identify and measure interactions between environmental parameters and the actors involved. With the decision-making process, we have obtained many results :i. following the formalization of multidimensional modeling, we have built an integrated datawarehouse that includes all the objects that are involved in managing the health risk - this model can be generalized to others vector-borne diseases;ii. despite a very wide variety of mosquitoes, Culex neavei, Aedes ochraceus and Aedes vexans are potential vectors of FVR. They are most present in the study area and, during the rainy season period which is most prone to suspected cases; the risk period still remains the month of October;iii. the analyzed ponds have almost the same behavior, but significant variations exist in some points.This research shows once again the interest in the discovery of relationships between environmental data and the FVR with datamining methods for the spatio-temporal monitoring of the risk of emergence
Bouba, Fanta. "Système d'information décisionnel sur les interactions environnement-santé : cas de la Fièvre de la Vallée du Rift au Ferlo (Sénégal)." Electronic Thesis or Diss., Paris 6, 2015. http://www.theses.fr/2015PA066461.
Full textOur research is in part of the QWeCI european project (Quantifying Weather and Climate Impacts on Health in Developing Countries, EU FP7) in partnership with UCAD, the CSE and the IPD, around the theme of environmental health with the practical case on vector-borne diseases in Senegal and particularly the Valley Fever (RVF). The health of human and animal populations is often strongly influenced by the environment. Moreover, research on spread factors of vector-borne diseases such as RVF, considers this issue in its dimension both physical and socio-economic. Appeared in 1912-1913 in Kenya, RVF is a widespread viral anthropo-zoonosis in tropical regions which concerns animals but men can also be affected. In Senegal, the risk area concerns mainly the Senegal River Valley and the forestry-pastoral areas Ferlo. With a Sahelian climate, the Ferlo has several ponds that are sources of water supply for humans and livestock but also breeding sites for potential vectors of RVF. The controlling of the RVF, which is crossroads of three (03) large systems (agro-ecological, pathogen, economic/health/social), necessarily entails consideration of several parameters if one wants to first understand the mechanisms emergence but also consider the work on risk modeling. Our work focuses on the decision making process for quantify the use of health data and environmental data in the impact assessment for the monitoring of RVF. Research teams involved produce data during their investigations periods and laboratory analyzes. The growing flood of data should be stored and prepared for correlated studies with new storage techniques such as datawarehouses. About the data analysis, it is not enough to rely only on conventional techniques such as statistics. Indeed, the contribution on the issue is moving towards a predictive analysis combining both aggregate storage techniques and processing tools. Thus, to discover information, it is necessary to move towards datamining. Furthermore, the evolution of the disease is strongly linked to environmental spatio-temporal dynamics of different actors (vectors, viruses, and hosts), cause for which we rely on spatio-temporal patterns to identify and measure interactions between environmental parameters and the actors involved. With the decision-making process, we have obtained many results :i. following the formalization of multidimensional modeling, we have built an integrated datawarehouse that includes all the objects that are involved in managing the health risk - this model can be generalized to others vector-borne diseases;ii. despite a very wide variety of mosquitoes, Culex neavei, Aedes ochraceus and Aedes vexans are potential vectors of FVR. They are most present in the study area and, during the rainy season period which is most prone to suspected cases; the risk period still remains the month of October;iii. the analyzed ponds have almost the same behavior, but significant variations exist in some points.This research shows once again the interest in the discovery of relationships between environmental data and the FVR with datamining methods for the spatio-temporal monitoring of the risk of emergence
Bottani, Simona. "Machine learning for neuroimaging using a very large scale clinical datawarehouse." Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS110.
Full textMachine learning (ML) and deep learning (DL) have been widely used for the computer-aided diagnosis (CAD) of neurodegenerative diseases The main limitation of these tools is that they have been mostly validated using research data sets that are very different from clinical routine ones. Clinical data warehouses (CDW) allow access to such clinical data.This PhD work consisted in applying ML/DL algorithms to data originating from the CDW of the Greater Paris area to validate CAD of neurodegenerative diseases.We developed, thanks to the manual annotation of 5500 images, an automatic approach for the quality control (QC) of T1-weighted (T1w) brain magnetic resonance images (MRI) from a clinical data set. QC is fundamental as insufficient image quality can prevent CAD systems from working properly. In the second work, we focused on the homogenization of T1w brain MRIs from a CDW. We proposed to homogenize such large clinical data set by converting images acquired after the injection of gadolinium into non-contrast-enhanced images. Lastly, we assessed whether ML/DL algorithms could detect dementia in a CDW using T1w brain MRI. We identified the population of interest using ICD-10 codes. We studied how the imbalance of the training sets may bias the results and we proposed strategies to attenuate these biases
Dony, Philippe. "CREATION D’UN ENTREPOT DE DONNEES EN ANESTHESIE: POTENTIEL POUR LA GESTION ET LA SANTE PUBLIQUE." Doctoral thesis, Universite Libre de Bruxelles, 2018. https://dipot.ulb.ac.be/dspace/bitstream/2013/279599/3/TM.pdf.
Full textDoctorat en Santé Publique
info:eu-repo/semantics/nonPublished
Nguyen, Benjamin. "Construction et évolution d'un entrepôt de données sur la toile." Paris 11, 2003. http://www.theses.fr/2003PA112283.
Full textOur work is to be placed in the general context of the creation of a framework in order to discover, analyse, process, store, integrate and query information found on the Web. We begin with a review of the state of the art concerning the following problems: querying information on the Web, managing the evolution of a warehouse, and document clustering techniques. In this thesis, we study the construction and evolution of a Web Warehouse. We propose on the one hand a methodology for conceiving such a warehouse, and on the other, we study the functionalities it should posess. We present the results of two experiments in which we took part, Xyleme and Thesus. The goal of the Xyleme Project was to manage all the XML pages of the Web, from crawling and fetching to querying. We detail in this work the monitoring of the pages, their temporal evolution. The goal of the Thesus Project was to create thematic collections of Web pages, based on the analysis of the page's semantics, using various tools, including link analysis and clustering algorithms. Both projects have been implemented, and our monitoring module is used in industry by the Xyleme S. A. Company. These two experiments provided a general framework for deeper reflection on how to conceive a thematic warehouse, which is detailled and illustrated by the SPIN prototype
Mathieu, Jean. "Intégration de données temps-réel issues de capteurs dans un entrepôt de données géo-décisionnel." Thesis, Université Laval, 2011. http://www.theses.ulaval.ca/2011/28019/28019.pdf.
Full textIn the last decade, the use of sensors for measuring various phenomenons has greatly increased. As such, we can now make use of sensors to measure GPS position, temperature and even the heartbeats of a person. Nowadays, the wide diversity of sensor makes them the best tools to gather data. Along with this effervescence, analysis tools have also advanced since the creation of transactional databases, leading to a new category of tools, analysis systems (Business Intelligence (BI)), which respond to the need of the global analysis of the data. Data warehouses and OLAP (On-Line Analytical Processing) tools, which belong to this category, enable users to analyze big volumes of data, execute time-based requests and build statistic graphs in a few simple mouse clicks. Although the various types of sensor can surely enrich any analysis, such data requires heavy integration processes to be driven into the data warehouse, centerpiece of any decision-making process. The different data types produced by sensors, sensor models and ways to transfer such data are even today significant obstacles to sensors data streams integration in a geo-decisional data warehouse. Also, actual geo-decisional data warehouses are not initially built to welcome new data on a high frequency. Since the performances of a data warehouse are restricted during an update, new data is usually added weekly, monthly, etc. However, some data warehouses, called Real-Time Data Warehouses (RTDW), are able to be updated several times a day without letting its performance diminish during the process. But this technology is not very common, very costly and in most of cases considered as "beta" versions. Therefore, this research aims to develop an approach allowing to publish and normalize real-time sensors data streams and to integrate it into a classic data warehouse. An optimized update strategy has also been developed so the frequent new data can be added to the analysis without affecting the data warehouse performances.
Atigui, Faten. "Approche dirigée par les modèles pour l’implantation et la réduction d’entrepôts de données." Thesis, Toulouse 1, 2013. http://www.theses.fr/2013TOU10044/document.
Full textOur work handles decision support systems based on multidimensional Data Warehouse (DW). A Data Warehouse (DW) is a huge amount of data, often historical, used for complex and sophisticated analysis. It supports the business process within an organization. The relevant data for the decision-making process are collected from data sources by means of software processes commonly known as ETL (Extraction-Transformation-Loading) processes. The study of existing systems and methods shows two major limits. Actually, when building a DW, the designer deals with two major issues. The first issue treats the DW's design, whereas the second addresses the ETL processes design. Current frameworks provide partial solutions that focus either on the multidimensional structure or on the ETL processes, yet both could benefit from each other. However, few studies have considered these issues in a unified framework and have provided solutions to automate all of these tasks. Since its creation, the DW has a large amount of data, mainly due to the historical data. Looking into the decision maker's analysis over time, we can see that they are usually less interested in old data.To overcome these shortcomings, this thesis aims to formalize the development of a time-varying (with a temporal dimension) DW from its design to its physical implementation. We use the Model Driven Engineering (MDE) that automates the process and thus significantly reduce development costs and improve the software quality. The contributions of this thesis are summarized as follows: 1. To formalize and to automate the development of a time-varying DW within a model-driven approach that provides: - A set of unified (conceptual, logical and physical) metamodels that describe data and transformation operations. - An OCL (Object Constraint Language) extension that aims to conceptually formalize the transformation operations. - A set of transformation rules that maps the conceptual model to logical and physical models. - A set of transformation rules that generates the code. 2. To formalize and to automate historical data reduction within a model-driven approach that provides : - A set of (conceptual, logical and physical) metamodels that describe the reduced data. - A set of reduction operations. - A set of transformation rules that implement these operations at the physical level.In order to validate our proposals, we have developed a prototype composed of three parts. The first part performs the transformation of models to lower level models. The second part transforms the physical model into code. The last part allows the DW reduction
Books on the topic "Entrepôt de données de santé"
Patrice, Boyer, ed. Dépression et santé publique: Données et réflexions. Paris: Acanthe, 1999.
Find full textZorn-Macrez, Caroline. Données de santé et secret partagé: Pour un droit de la personne à la protection de ses données de santé partagées. Nancy: Presses universitaires de Nancy, 2010.
Find full textFlueckiger, Christian. Dopage, santé des sportifs professionnels et protection des données médicales. [Bruxelles]: Bruylant, 2008.
Find full text1954-, Morin Diane, and Association francophone pour le savoir-Acfas., eds. La pratique professionnelle en santé: Données, résultats et savoirs probants. Montréal, Qué: Association francophone pour le savoir-Acfas, 2003.
Find full textDavid, Pierre. L' appriement de données échantillonnales et administratives en vue d'étudier les déterminants de la santé. Ottawa, Ont: Statistique Canada, 1993.
Find full textColloque la condition des femmes immigrantes (en savoir davantage (1989 Montréal, Québec). Actes du colloque: La condition des femmes immigrantes : en savoir davantage : faits actuels et données récentes. Montréal, Qué: Éditions Communiqu'elles, 1989.
Find full textStatistique Canada. Direction des études analytiques. Système de statistiques relatives à la santé: Proposition d'un nouveau cadre théorique visant l'intégration de données relatives à la santé. S.l: s.n, 1987.
Find full textFalissard, Bruno. Mesurer la subjectivité en santé: Perspective méthodologique et statistique. Paris: Masson, 2001.
Find full textRoy, Sylvie. Pour améliorer les pratiques éducatives : des données d'enquête sur les jeunes. [Québec]: Ministère de l'éducation, 2003.
Find full textDanièle, Paquette-Desjardins, and Paquette-Desjardins formation-conseil, eds. La collecte de données: Explorer et comprendre la situation de santé avec le client/famille. Montréal: Chenelière/McGraw-Hill, 2002.
Find full textBook chapters on the topic "Entrepôt de données de santé"
Staccini, P., C. Daniel, and P. Gillois. "Les données de santé et les dossiers médicaux partagés." In Informatique médicale, e-Santé, 331–55. Paris: Springer Paris, 2013. http://dx.doi.org/10.1007/978-2-8178-0338-8_13.
Full textGoetz, Christophe, Aurélien Zang, and Nicolas Jay. "Apports d’une méthode de fouille de données pour la détection des cancers du sein incidents dans les données du programme de médicalisation des systèmes d’information." In Informatique et Santé, 189–99. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0285-5_17.
Full textJonquet, Clément, Nigam Shah, and Mark A. Musen. "Un service Web pour l’annotation sémantique de données biomédicales avec des ontologies." In Informatique et Santé, 151–62. Paris: Springer Paris, 2009. http://dx.doi.org/10.1007/978-2-287-99305-3_14.
Full textQuantin, C., F. A. Allaert, B. Auverlot, and V. Rialle. "Sécurité, aspects juridiques et éthiques des données de santé informatisées." In Informatique médicale, e-Santé, 265–305. Paris: Springer Paris, 2013. http://dx.doi.org/10.1007/978-2-8178-0338-8_11.
Full textBourdé, Annabel, Marc Cuggia, Théo Ouazine, Bruno Turlin, Oussama Zékri, Catherine Bohec, and Régis Duvauferrier. "Vers la définition automatique des éléments de données des fiches RCP en cancérologie à partir d’une ontologie." In Informatique et Santé, 121–30. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0285-5_11.
Full textBayat, Sahar, Marc Cuggia, Delphine Rossille, and Luc Frimar. "Prédire l’accès à la liste d’attente de transplantation rénale: comparaison de deux méthodes de fouille de données." In Informatique et Santé, 239–50. Paris: Springer Paris, 2009. http://dx.doi.org/10.1007/978-2-287-99305-3_22.
Full textDibad, Ahmed-Diouf Dirieh, Lina F. Soualmia, Tayeb Merabti, Julien Grosjean, Saoussen Sakji, Philippe Massari, and Stéfan J. Darmoni. "Un modèle de données adapté à la recherche d’information dans le dossier patient informatisé: Étude, conception et évaluation." In Informatique et Santé, 251–62. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0285-5_22.
Full textMetzger, Marie-Hélène, Quentin Gicquel, Ivan Kergourlay, Camille Cluze, Bruno Grandbastien, Yasmina Berrouane, Marie-Pierre Tavolacci, Frédérique Segond, Suzanne Pereira, and Stéfan J. Darmoni. "Codage standardisé de données médicales textuelles à l’aide d’un serveur multi-terminologique de santé: Exemple d’application en épidémiologie hospitalière." In Informatique et Santé, 109–19. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0285-5_10.
Full textCampillo-Gimenez, Boris, Marc Cuggia, Anita Burgun, and Pierre Le Beux. "La qualité des données médicales dans les dossiers patient de deux services d’accueil des urgences avant et après informatisation." In Informatique et Santé, 331–42. Paris: Springer Paris, 2011. http://dx.doi.org/10.1007/978-2-8178-0285-5_29.
Full textCuggia, M., P. Avillach, and C. Daniel. "La représentation des données des patients dans un système d’information de santé et dans le Dossier Patient Informatisé." In Informatique médicale, e-Santé, 71–99. Paris: Springer Paris, 2013. http://dx.doi.org/10.1007/978-2-8178-0338-8_4.
Full textConference papers on the topic "Entrepôt de données de santé"
A, Shyaka, Kabongo F, Tolno C, Barry I, and Bachy C. "Evaluation des occasions manquées de vaccination (OMV) chez les enfants de 0-59 mois dans 4 établissements de santé de Matoto, Guinée." In MSF Paediatric Days 2024. NYC: MSF-USA, 2024. http://dx.doi.org/10.57740/ktmpcj.
Full textRoume, M., S. Azogui-Lévy, G. Lescaille, V. Descroix, and J. Rochefort. "Connaissances, attitudes et pratiques en pathologie de la muqueuse buccale des chirurgiens-dentistes en France, enquête nationale." In 66ème Congrès de la SFCO. Les Ulis, France: EDP Sciences, 2020. http://dx.doi.org/10.1051/sfco/20206602010.
Full textNoaillon, E., S. Azogui-Lévy, G. Lescaille, R. Toledo, V. Descroix, P. Goudot, and J. Rochefort. "Impact des recommandations de l’ANSM dans la prise en charge en cabinet libéral des collections circonscrites aiguës suppurées de la cavité orale d’origine dentaire : enquête nationale." In 66ème Congrès de la SFCO. Les Ulis, France: EDP Sciences, 2020. http://dx.doi.org/10.1051/sfco/20206602017.
Full textLan, R., F. Campana, J. H. Catherine, U. Ordioni, and D. Tardivo. "Nouvelles techniques d’aide au diagnostic des lésions pré-cancéreuses et cancéreuses de la cavité orale : revue systématique et résultats préliminaires." In 66ème Congrès de la SFCO. Les Ulis, France: EDP Sciences, 2020. http://dx.doi.org/10.1051/sfco/20206602018.
Full textReports on the topic "Entrepôt de données de santé"
de Lamotte, Frédéric, Véronique Stoll, Cécile Arenes, Marie-Emilia Herbert, Stéphane Debard, Françoise Genova, Christine Hadrossek, et al. Sélectionner un entrepôt thématique de confiance pour le dépôt de données : méthodologie et analyse de l'offre existante. Ministère de l’enseignement supérieur et de la recherche, March 2024. http://dx.doi.org/10.52949/52.
Full textMcAdams-Roy, Kassandra, Philippe Després, and Pierre-Luc Déziel. La gouvernance des données dans le domaine de la santé : Pour une fiducie de données au Québec ? Observatoire international sur les impacts sociétaux de l’intelligence artificielle et du numérique, February 2023. http://dx.doi.org/10.61737/nrvw8644.
Full textRégis, Catherine, Gabrielle Beetz, Janine Badr, Alexandre Castonguay, Martin Cousineau, Philippe Després, Joé T. Martineau, Aude Motulsky, Jean Noel Nikiema, and Cécile Petitgand. Aspects juridiques de l’IA en santé - Fiche 3Aspects juridiques de l’IA en santé - Fiche 3. Observatoire international sur les impacts sociétaux de l’intelligence artificielle et du numérique, March 2022. http://dx.doi.org/10.61737/ulfz6546.
Full textde Marcellis-Warin, Nathalie, and Christophe Mondin. Baromètre Santé CIRANO – OBVIA : un outil pour comprendre les déterminants de l’acceptabilité sociale du partage des données et l’utilisation de l’IA en santé. Observatoire international sur les impacts sociétaux de l'IA et du numérique, November 2022. http://dx.doi.org/10.61737/xchv3269.
Full textMartineau, Joé T., Frédérique Romy Godin, Janine Badr, Alexandre Castonguay, Martin Cousineau, Philippe Després, Aude Motulsky, Jean Noel Nikiema, Cécile Petitgand, and Catherine Régis. Enjeux éthiques de l’IA en santé - Fiche 4. Observatoire international sur les impacts sociétaux de l'IA et du numérique, March 2022. http://dx.doi.org/10.61737/fspn5441.
Full textKaboré, Gisele, and Idrissa Kabore. Analyse secondaire des données de l'analyse situationnelle des services de santé de la reproduction. Population Council, 2009. http://dx.doi.org/10.31899/pgy20.1000.
Full textJabet, Carole, and Cécile Petitgand. Propositions de principes directeurs : Concilier l'acceptabilité sociale active à l'utilisation secondaire des renseignements personnels sur la santé. Observatoire international sur les impacts sociétaux de l’intelligence artificielle et du numérique, September 2022. http://dx.doi.org/10.61737/yogf7213.
Full textBourassa Forcier, Mélanie, Dary-Anne Tourangeau, Gaëlle Feruzi, and Mathieu Kiriakos. Introduction d’un télérobot en résidences privées : Enjeux légaux et organisationnels. CIRANO, April 2022. http://dx.doi.org/10.54932/obpe9357.
Full textSamochowiec, Jakub, and Andreas Müller. La montre connectée nuit-elle à la solidarité? – Scénarios pour un système de santé basé sur les données. Gdi-verlag, Gottlieb Duttweiler Institute, 2021. http://dx.doi.org/10.59986/xjjq2019.
Full textLarrieu, Maxence. Pour quelles revues et publishers les chercheurs d'une université pluridisciplinaire travaillent-ils ? Université Paris Cité, September 2023. http://dx.doi.org/10.53480/luoj2939.
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