Overcoming Therapeutic Inertia in Type 2 Diabetes: Exploring Machine Learning-Based Scenario Simulation for Improving Short-Term Glycemic Control

Overcoming Therapeutic Inertia in Type 2 Diabetes: Exploring Machine Learning-Based Scenario Simulation for Improving Short-Term Glycemic Control

Background: International guidelines for diabetes care emphasize the urgency of promptly achieving and sustaining adequate glycemic control to reduce the occurrence of micro/macrovascular complications in patients with type 2 diabetes mellitus (T2DM). However, data from the Italian Association of Me...

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Bibliographic Details
Main Authors: Musacchio Nicoletta, Rita Zilich, Davide Masi, Fabio Baccetti, Besmir Nreu, Carlo Bruno Giorda, Giacomo Guaita, Lelio Morviducci, Marco Muselli, Alessandro Ozzello, Federico Pisani, Paola Ponzani, Antonio Rossi, Pierluigi Santin, Damiano Verda, Graziano Di Cianni, Riccardo Candido
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Machine Learning and Knowledge Extraction
Subjects:
machine learning
artificial intelligence
type 2 diabetes
therapeutic inertia
insulin
Online Access:https://www.mdpi.com/2504-4990/6/1/21

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https://www.mdpi.com/2504-4990/6/1/21

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