Letteratura scientifica selezionata sul tema "Heterogeneous health data"
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Articoli di riviste sul tema "Heterogeneous health data"
Li, Gang-Guo, e Zheng-Zhi Wang. "Incorporating heterogeneous biological data sources in clustering gene expression data". Health 01, n. 01 (2009): 17–23. http://dx.doi.org/10.4236/health.2009.11004.
Testo completoMohammed, Noman, Xiaoqian Jiang, Rui Chen, Benjamin C. M. Fung e Lucila Ohno-Machado. "Privacy-preserving heterogeneous health data sharing". Journal of the American Medical Informatics Association 20, n. 3 (13 dicembre 2012): 462–69. http://dx.doi.org/10.1136/amiajnl-2012-001027.
Testo completoHadzi-Pavlovic, Dusan. "Correlations III: heterogeneous data". Acta Neuropsychiatrica 19, n. 3 (giugno 2007): 215–16. http://dx.doi.org/10.1111/j.1601-5215.2007.00219.x.
Testo completoSunindyo, Wikan Danar, Thomas Moser, Dietmar Winkler e Stefan Biffl. "Analyzing OSS Project Health with Heterogeneous Data Sources". International Journal of Open Source Software and Processes 3, n. 4 (ottobre 2011): 1–23. http://dx.doi.org/10.4018/jossp.2011100101.
Testo completoZhao, Jing, Panagiotis Papapetrou, Lars Asker e Henrik Boström. "Learning from heterogeneous temporal data in electronic health records". Journal of Biomedical Informatics 65 (gennaio 2017): 105–19. http://dx.doi.org/10.1016/j.jbi.2016.11.006.
Testo completoGanguly, Sukanta, Pavandeep Kataria, Radmila Juric, Atila Ertas e Murat M. Tanik. "Sharing Information and Data Across Heterogeneous e-Health Systems". Telemedicine and e-Health 15, n. 5 (giugno 2009): 454–64. http://dx.doi.org/10.1089/tmj.2008.0149.
Testo completoMonga, H. K., e T. B. Patrick. "Error estimation in linking heterogeneous data sources". Health Informatics Journal 7, n. 3-4 (settembre 2001): 135–37. http://dx.doi.org/10.1177/146045820100700305.
Testo completoBleischwitz, Sinja, Tristan Salomon Winkelmann, Yvonne Pfeifer, Martin Alexander Fischer, Niels Pfennigwerth, Jens André Hammerl, Ulrike Binsker et al. "Antimicrobial Resistance Surveillance: Data Harmonisation and Data Selection within Secondary Data Use". Antibiotics 13, n. 7 (16 luglio 2024): 656. http://dx.doi.org/10.3390/antibiotics13070656.
Testo completoParagliola, Giovanni, e Patrizia Ribino. "Exploring heterogeneous data distribution issues in e-health federated systems". Biomedical Signal Processing and Control 92 (giugno 2024): 106039. http://dx.doi.org/10.1016/j.bspc.2024.106039.
Testo completoLi, Ruohong, Honglang Wang e Wanzhu Tu. "Robust estimation of heterogeneous treatment effects using electronic health record data". Statistics in Medicine 40, n. 11 (19 marzo 2021): 2713–52. http://dx.doi.org/10.1002/sim.8926.
Testo completoTesi sul tema "Heterogeneous health data"
Nugawela, Saliya. "Data warehousing model for integrating fragmented electronic health records from disparate and heterogeneous clinical data stores". Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/60880/1/Saliya_Nugawela_Thesis.pdf.
Testo completoWootton, Adam J. "Fusion of heterogeneous data in non-destructive testing and structural health monitoring using Echo State Networks". Thesis, Keele University, 2018. http://eprints.keele.ac.uk/5004/.
Testo completoGriffier, Romain. "Intégration et utilisation secondaire des données de santé hospitalières hétérogènes : des usages locaux à l'analyse fédérée". Electronic Thesis or Diss., Bordeaux, 2024. http://www.theses.fr/2024BORD0479.
Testo completoHealthcare data can be used for purposes other than those for which it was initially collected: this is the secondary use of health data. In the hospital context, to overcome the obstacles to secondary use of healthcaree data (data and organizational barriers), a classic strategy is to set up Clinical Data Warehouses (CDWs). This thesis describes three contributions to the Bordeaux University Hospital’s CDW. Firstly, an instance-based, privacy-preserving, method for mapping numerical biology data elements is presented, with an F-measure of 0,850, making it possible to reduce the semantic heterogeneity of data. Next, an adaptation of the i2b2 clinical data integration model is proposed to enable CDW data persistence in a NoSQL database, Elasticsearch. This implementation has been evaluated on the Bordeaux University Hospital’s CDW, showing improved performance in terms of storage and query time, compared with a relational database. Finally, the Bordeaux University Hospital’s CDW environment is presented, with the description of a first CDW dedicated to local uses that can be used autonomously by end users (i2b2), and a second CDW dedicated to federated networks (OMOP) enabling participation in the DARWIN-EU federated network
McInerney, Sean. "Parameterising continuum models of heat transfer in heterogeneous living skin using experimental data". Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/123772/1/Sean_McInerney_Thesis.pdf.
Testo completoDarbon, Alexandre. "Épidémiologie sur réseau pour l'évaluation des risques dans la prévention et le contrôle des infections Network-based assessment of the vulnerability of Italian regions to bovine brucellosis Disease persistence on temporal contact networks accounting for heterogeneous infectious periods". Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS077.
Testo completoMy doctoral thesis aims to propose solutions against the spread of infectious diseases in specific contexts, taking into account how host contacts evolve in time using a temporal network representation. It focuses on the determination of the epidemic threshold, a key indicator of the epidemic risk. By leveraging and extending a mathematical formalism from network theory, this work enables the computation of the epidemic threshold in real situations in order to identify public health measures. A first project addresses the persistence of bovine brucellosis in Italy despite the existing eradication measures. Using comprehensive data on cattle movements between Italian farms over several years, as well as time-stamped outbreak records, the epidemic threshold computation in each region of the country provides information on regions vulnerability and proposes factors that may explain disease persistence. An extension of the formalism is then presented, including heterogeneous average infectious periods in the epidemic threshold computation. This work shows in different epidemiological contexts how the classical assumption that the average infectious period is the same for all hosts in a population may bias epidemic risk assessments. This method also identifies the hosts in a population that are primarily responsible for the global epidemic risk
Ayvazyan, Vigen. "Etude de champs de température séparables avec une double décomposition en valeurs singulières : quelques applications à la caractérisation des propriétés thermophysiques des matérieux et au contrôle non destructif". Thesis, Bordeaux 1, 2012. http://www.theses.fr/2012BOR14671/document.
Testo completoInfrared thermography is a widely used method for characterization of thermophysical properties of materials. The advent of the laser diodes, which are handy, inexpensive, with a broad spectrum of characteristics, extend metrological possibilities of infrared cameras and provide a combination of new powerful tools for thermal characterization and non destructive evaluation. However, this new dynamic has also brought numerous difficulties that must be overcome, such as high volume noisy data processing and low sensitivity to estimated parameters of such data. This requires revisiting the existing methods of signal processing, adopting new sophisticated mathematical tools for data compression and processing of relevant information.New strategies consist in using orthogonal transforms of the signal as a prior data compression tools, which allow noise reduction and control over it. Correlation analysis, based on the local cerrelation study between partial derivatives of the experimental signal, completes these new strategies. A theoretical analogy in Fourier space has been performed in order to better understand the «physical» meaning of modal approaches.The response to the instantaneous point source of heat, has been revisited both numerically and experimentally. By using separable temperature fields, a new inversion technique based on a double singular value decomposition of experimental signal has been introduced. In comparison with previous methods, it takes into account two or three-dimensional heat diffusion and therefore offers a better exploitation of the spatial content of infrared images. Numerical and experimental examples have allowed us to validate in the first approach our new estimation method of longitudinal thermal diffusivities. Non destructive testing applications based on the new technique have also been introduced.An old issue, which consists in determining the initial temperature field from noisy data, has been approached in a new light. The necessity to know the thermal diffusivities of an orthotropic medium and the need to take into account often three-dimensional heat transfer, are complicated issues. The implementation of the double singular value decomposition allowed us to achieve interesting results according to its ease of use. Indeed, modal approaches are statistical methods based on high volume data processing, supposedly robust as to the measurement noise
Pivovarov, Rimma. "Electronic Health Record Summarization over Heterogeneous and Irregularly Sampled Clinical Data". Thesis, 2015. https://doi.org/10.7916/D89W0F6V.
Testo completo"Novel Statistical Learning Methods for Multi-Modality Heterogeneous Data Fusion in Health Care Applications". Doctoral diss., 2019. http://hdl.handle.net/2286/R.I.53553.
Testo completoDissertation/Thesis
Doctoral Dissertation Industrial Engineering 2019
Hoklas, Megan Marie. "An integrated latent construct modeling framework for predicting physical activity engagement and health outcomes". Thesis, 2014. http://hdl.handle.net/2152/28257.
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Libri sul tema "Heterogeneous health data"
Pivovarov, Rimma. Electronic Health Record Summarization over Heterogeneous and Irregularly Sampled Clinical Data. [New York, N.Y.?]: [publisher not identified], 2015.
Cerca il testo completoNilipour, Reza. Neurolinguistics. A cura di Anousha Sedighi e Pouneh Shabani-Jadidi. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198736745.013.18.
Testo completoCapitoli di libri sul tema "Heterogeneous health data"
Ali, Rafat, e Nida Jamil Khan. "Networks Analytics of Heterogeneous Big Data". In Biological Networks in Human Health and Disease, 65–74. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-4242-8_4.
Testo completoSavoska, Snezana, Blagoj Ristevski e Vladimir Trajkovik. "Personal Health Record Data-Driven Integration of Heterogeneous Data". In Data-Intensive Research, 1–21. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-5184-8_1.
Testo completoRen, Peng, Weihang Lin, Ye Liang, Ruoyu Wang, Xingyue Liu, Baifu Zuo, Tan Chen, Xin Li, Ming Sheng e Yong Zhang. "HMDFF: A Heterogeneous Medical Data Fusion Framework Supporting Multimodal Query". In Health Information Science, 254–66. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-90885-0_23.
Testo completoXiao, Qi, Wenkui Zheng, Chenyu Mao, Wei Hou, Hao Lan, Daojun Han, Yang Duan, Peng Ren e Ming Sheng. "MHDML: Construction of a Medical Lakehouse for Multi-source Heterogeneous Data". In Health Information Science, 127–35. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20627-6_12.
Testo completoCui, Qin, Wenkui Zheng, Wei Hou, Ming Sheng, Peng Ren, Wang Chang e XiangYang Li. "HoloCleanX: A Multi-source Heterogeneous Data Cleaning Solution Based on Lakehouse". In Health Information Science, 165–76. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20627-6_16.
Testo completoAsadzadehzanjani, Negin, e Janusz Wojtusiak. "Administrative Health Data Representation for Mortality and High Utilization Prediction". In Heterogeneous Data Management, Polystores, and Analytics for Healthcare, 133–50. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-93663-1_11.
Testo completoKale, Geetanjali, e Kalyani Waghmare. "Heterogeneous data management in IoT-based health care systems". In Artificial Intelligence for Internet of Things, 49–64. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003335801-4.
Testo completoDubovitskaya, Alevtina, Petr Novotny, Scott Thiebes, Ali Sunyaev, Michael Schumacher, Zhigang Xu e Fusheng Wang. "Intelligent Health Care Data Management Using Blockchain: Current Limitation and Future Research Agenda". In Heterogeneous Data Management, Polystores, and Analytics for Healthcare, 277–88. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33752-0_20.
Testo completoGardner, P. A., L. A. Bull, N. Dervilis e K. Worden. "On the Application of Heterogeneous Transfer Learning to Population-Based Structural Health Monitoring". In Data Science in Engineering, Volume 9, 87–98. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76004-5_11.
Testo completoGardner, P. A., L. A. Bull, N. Dervilis e K. Worden. "On the Application of Heterogeneous Transfer Learning to Population-Based Structural Health Monitoring". In Data Science in Engineering, Volume 9, 87–98. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76004-5_11.
Testo completoAtti di convegni sul tema "Heterogeneous health data"
Hu, Hengrui, Anai N. Kothari e Anjishnu Banerjee. "Personalized Federated Learning for Gastric Cancer: Adaptive Inference from Large Heterogeneous Piecewise Electronic Health Record Based Biomedical Data". In 2024 IEEE International Conference on Big Data (BigData), 4554–63. IEEE, 2024. https://doi.org/10.1109/bigdata62323.2024.10825882.
Testo completoZheng, Yuhui, Yankun Zhang, Weiqiang Lin e Qingfeng Wu. "How Can We Design a Standardized and Efficient Health Data Management System for Large-Scale Heterogeneous TCM Data?" In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 4848–53. IEEE, 2024. https://doi.org/10.1109/bibm62325.2024.10822299.
Testo completoZhao, Haotian, Bin Wang, Qinglai Guo, Yixun Xue, Yaqi Sun e Hongbin Sun. "Hybrid Model-and-Data-Driven Combined Heat and Power Economic Dispatch Based on Heterogeneous Decomposition". In 2024 IEEE Power & Energy Society General Meeting (PESGM), 1–5. IEEE, 2024. http://dx.doi.org/10.1109/pesgm51994.2024.10689144.
Testo completoLiu, Zheng, Xiaohan Li, Hao Peng, Lifang He e Philip S. Yu. "Heterogeneous Similarity Graph Neural Network on Electronic Health Records". In 2020 IEEE International Conference on Big Data (Big Data). IEEE, 2020. http://dx.doi.org/10.1109/bigdata50022.2020.9377795.
Testo completoKiourtis, Athanasios, Argyro Mavrogiorgou e Dimosthenis Kyriazis. "Aggregating Heterogeneous Health Data through an Ontological Common Health Language". In 2017 10th International Conference on Developments in eSystems Engineering (DeSE). IEEE, 2017. http://dx.doi.org/10.1109/dese.2017.9.
Testo completoSUN, HAO, e ORAL BUYUKOZTURK. "Heterogeneous Data Fusion for Traffic-induced Excitation Identification of Truss Bridges". In Structural Health Monitoring 2015. Destech Publications, 2015. http://dx.doi.org/10.12783/shm2015/47.
Testo completoFan, Kai, Marisa Eisenberg, Alison Walsh, Allison Aiello e Katherine Heller. "Hierarchical Graph-Coupled HMMs for Heterogeneous Personalized Health Data". In KDD '15: The 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2783258.2783326.
Testo completoLu, Xuchen, Hongling Tang, Wenli Cheng e Tingting Zhang. "Heterogeneous Data Source Middleware for Android E-Health Application". In 2012 Eighth International Conference on Mobile Ad-hoc and Sensor Networks (MSN). IEEE, 2012. http://dx.doi.org/10.1109/msn.2012.16.
Testo completoTomoda, Kyosuke, Kai Morino, Hiroshi Murata, Ryo Asaoka e Kenji Yamanishi. "Predicting Glaucomatous Progression with Piecewise Regression Model from Heterogeneous Medical Data". In 9th International Conference on Health Informatics. SCITEPRESS - Science and and Technology Publications, 2016. http://dx.doi.org/10.5220/0005703900930104.
Testo completoDao, Minh-Son, e Koji Zettsu. "Discovering Environmental Impacts on Public Health Using Heterogeneous Big Sensory Data". In 2015 IEEE International Congress on Big Data (BigData Congress). IEEE, 2015. http://dx.doi.org/10.1109/bigdatacongress.2015.122.
Testo completoRapporti di organizzazioni sul tema "Heterogeneous health data"
Cerda, Maikol, David Cervantes, Paul Gertler, Sean Higgins, Ana María Montoya, Eric Parrado, Carlos Serrano, Raimundo Undurraga e Patricia Yáñez-Pagans. Covid-19 Pandemic and SMEs' Performance in Latin America. Inter-American Development Bank, febbraio 2023. http://dx.doi.org/10.18235/0004720.
Testo completoColombo, Karina, Elisa Failache e Martina Querejeta. High-Speed Internet and Socioemotional Wellbeing in Uruguayan Youth. Inter-American Development Bank, novembre 2023. http://dx.doi.org/10.18235/0005154.
Testo completovan de Sand, Ron, e Jörg Reiff-Stephan. FrostByte Dataset. Technische Hochschule Wildau, 2021. http://dx.doi.org/10.15771/1894.
Testo completoMurad, M. Hassan, Stephanie M. Chang, Celia Fiordalisi, Jennifer S. Lin, Timothy J. Wilt, Amy Tsou, Brian Leas et al. Improving the Utility of Evidence Synthesis for Decision Makers in the Face of Insufficient Evidence. Agency for Healthcare Research and Quality (AHRQ), aprile 2021. http://dx.doi.org/10.23970/ahrqepcwhitepaperimproving.
Testo completoKingston, A. W., A. Mort, C. Deblonde e O H Ardakani. Hydrogen sulfide (H2S) distribution in the Triassic Montney Formation of the Western Canadian Sedimentary Basin. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329797.
Testo completoShpigel, Nahum Y., Ynte Schukken e Ilan Rosenshine. Identification of genes involved in virulence of Escherichia coli mastitis by signature tagged mutagenesis. United States Department of Agriculture, gennaio 2014. http://dx.doi.org/10.32747/2014.7699853.bard.
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