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Potential predictors of type-2 diabetes risk: machine learning, synthetic data and wearable health devices

Paola Stolfi1, Ilaria Valentini2, Maria Concetta Palumbo3

  • 1Institute for Applied Mathematics, National Research Council of Italy, Rome, Italy. p.stolfi@iac.cnr.it.

BMC Bioinformatics
|December 14, 2020
PubMed
Abstract

Keywords:
Computational modelingEmulatorMachine learningRandom forestSynthetic dataT2D

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