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Clustering of elderly patient subgroups to identify medication-related readmission risks.

, , , , and . Int. J. Medical Informatics, 85 (1): 43-52 (2016)

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Clustering of elderly patient subgroups to identify medication-related readmission risks., , , , and . Int. J. Medical Informatics, 85 (1): 43-52 (2016)A pattern mining based integrative framework for biomarker discovery., , , , , and . BCB, page 498-505. ACM, (2012)Predicting the Factors of Improvement of Health Status of Home Health Care Patients: A Holistic Data Mining Approach., , , , , , , and . AMIA, AMIA, (2015)Evaluation of BER/PER Performance of a FLAMINGO Network., and . AACC, volume 3285 of Lecture Notes in Computer Science, page 191-197. Springer, (2004)Finding Causal Mechanistic Drug-Drug Interactions from Observational Data., , , , , and . AMIA, AMIA, (2020)Data Mining Methodologies to Discover Best practices for Diabetic Patients with Health Disparities., , , , , , , , , and . AMIA, AMIA, (2014)Estimating Causal Multi-Drug-Drug Interaction for Adverse Drug Reactions., , , , and . AMIA, AMIA, (2018)Estimating Personalized Drug Effects with Longitudinal Observational Data., , and . AMIA, AMIA, (2018)Predicting adverse drug reactions through interpretable deep learning framework., , , , and . BMC Bioinform., 19-S (21): 476:1-476:13 (2018)Interpretable Drug Target Prediction Using Deep Neural Representation., , , , , and . IJCAI, page 3371-3377. ijcai.org, (2018)