Predictive modeling for the development of diabetes mellitus using key factors in various machine learning approaches

Predictive modeling for the development of diabetes mellitus using key factors in various machine learning approaches

Aims: Machine learning (ML) approaches are beneficial when automatic identification of relevant features among numerous candidates is desired. We investigated the predictive ability of several ML models for new onset of diabetes mellitus. Methods: In 10,248 subjects who received annual health examin...

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Bibliographic Details
Main Authors: Marenao Tanaka, Yukinori Akiyama, Kazuma Mori, Itaru Hosaka, Kenichi Kato, Keisuke Endo, Toshifumi Ogawa, Tatsuya Sato, Toru Suzuki, Toshiyuki Yano, Hirofumi Ohnishi, Nagisa Hanawa, Masato Furuhashi
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Diabetes Epidemiology and Management
Subjects:
Artificial intelligence
Machine learning
Diabetes mellitus
Fatty liver index
Online Access:http://www.sciencedirect.com/science/article/pii/S2666970623000707

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