Michele Bernardini
Macerata, Italy
Last Updated: 09/26/2026
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Found 9 publications
A machine learning algorithm for the prediction of complications incorporated in electronic medical records improves type 2 diabetes care.
Journal: Diabetes research and clinical practice
Published: June 18, 2025
A novel missing data imputation approach based on clinical conditional Generative Adversarial Networks applied to EHR datasets.
Journal: Computers in biology and medicine
Published: April 27, 2023
Prediction of complications of type 2 Diabetes: A Machine learning approach.
Journal: Diabetes research and clinical practice
Published: May 26, 2022
Machine learning using the extreme gradient boosting (XGBoost) algorithm predicts 5-day delta of SOFA score at ICU admission in COVID-19 patients.
Journal: Journal of intensive medicine
Published: June 25, 2021
A Semi-Supervised Multi-Task Learning Approach for Predicting Short-Term Kidney Disease Evolution.
Journal: IEEE journal of biomedical and health informatics
Published: April 20, 2021
A Decision Support System for Diabetes Chronic Care Models Based on General Practitioner Engagement and EHR Data Sharing.
Journal: IEEE journal of translational engineering in health and medicine
Published: May 13, 2020
Early temporal prediction of Type 2 Diabetes Risk Condition from a General Practitioner Electronic Health Record: A Multiple Instance Boosting Approach.
Journal: Artificial intelligence in medicine
Published: July 29, 2019
TyG-er: An ensemble Regression Forest approach for identification of clinical factors related to insulin resistance condition using Electronic Health Records.
Journal: Computers in biology and medicine
Published: May 21, 2019
Discovering the Type 2 Diabetes in Electronic Health Records Using the Sparse Balanced Support Vector Machine.
Journal: IEEE journal of biomedical and health informatics
Published: February 15, 2019
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Last Updated: 09/26/2026