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Improving Clinical Decisions on T2DM Patients Integrating Clinical, Administrative and Environmental Data.

, , , , , , , and . MedInfo, volume 216 of Studies in Health Technology and Informatics, page 682-686. IOS Press, (2015)

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Improving Clinical Decisions on T2DM Patients Integrating Clinical, Administrative and Environmental Data., , , , , , , and . MedInfo, volume 216 of Studies in Health Technology and Informatics, page 682-686. IOS Press, (2015)Big Data as a Driver for Clinical Decision Support Systems: A Learning Health Systems Perspective., , , , , , , , , and 2 other author(s). Frontiers Digit. Humanit., (2018)Temporal data mining and process mining techniques to identify cardiovascular risk-associated clinical pathways in Type 2 diabetes patients., , , , , , , and . BHI, page 240-243. IEEE, (2014)Hierarchical Bayesian Logistic Regression to forecast metabolic control in type 2 DM patients., , , , , , , , and . AMIA, AMIA, (2016)Supervised Implementation of Guidelines for Diabetes Management on the World Wide Web., , , , , , and . AMIA, AMIA, (2001)Template for preparation of papers for IEEE sponsored conferences & symposia., , , , , , , and . EMBC, page 2123-2126. IEEE, (2015)Multi-access Services for the Management of Diabetes Mellitus: The M2DM Project., , , , , , , , , and 21 other author(s). AMIA, AMIA, (2002)A dashboard-based system for supporting diabetes care., , , , , , , , , and 5 other author(s). J. Am. Medical Informatics Assoc., 25 (5): 538-547 (2018)Clustering Cardiovascular Risk Trajectories of Patients with Type 2 Diabetes Using Process Mining., , , , , , , and . EMBC, page 341-344. IEEE, (2019)