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Risk Assessment Models for Diabetes Complications: A Survey of Available Online Tools.

, , , , and . MobiHealth, volume 83 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 46-53. Springer, (2011)

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Risk Assessment Models for Diabetes Complications: A Survey of Available Online Tools., , , , and . MobiHealth, volume 83 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 46-53. Springer, (2011)A systematic review of predictive risk models for diabetes complications based on large scale clinical studies, , , , and . Journal of Diabetes and Its Complications, (2013)T-ReCS: stable selection of dynamically formed groups of features with application to prediction of clinical outcomes., , , , and . Pacific Symposium on Biocomputing (PSB), (2014)A vision and strategy for the virtual physiological human: 2012 update, , , , , , , , , and 14 other author(s). Interface Focus, (2013)Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning., , and . KDD, page 915-924. ACM, (2015)Scoring Bayesian Networks with Informative, Causal and Associative Priors, and . CoRR, (2012)Feature Selection with the R Package MXM: Discovering Statistically Equivalent Feature Subsets, , , , and . Journal of Statistical Software, (2017)Bootstrapping the out-of-sample predictions for efficient and accurate cross-validation, , and . Machine Learning, 107 (12): 1895--1922 (Dec 1, 2018)A unified approach for sparse dynamical system inference from temporal measurements, and . Bioinformatics, (January 2019)SCENERY: a web application for (causal) network reconstruction from cytometry data, , , , , , , and . Nucleic Acids Research, (July 2017)