This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (2828) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (916) Machine Learning (1741) Demographics of Users, Social & Digital Divide (835) Obesity and Nutrition as Public Health Problem (349)

Published on in Vol 6, No 12 (2022): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40404, first published .
Predicting Overweight and Obesity Status Among Malaysian Working Adults With Machine Learning or Logistic Regression: Retrospective Comparison Study

Predicting Overweight and Obesity Status Among Malaysian Working Adults With Machine Learning or Logistic Regression: Retrospective Comparison Study

Predicting Overweight and Obesity Status Among Malaysian Working Adults With Machine Learning or Logistic Regression: Retrospective Comparison Study

Authors of this article:

Jyh Eiin Wong1 Author Orcid Image ;   Miwa Yamaguchi2 Author Orcid Image ;   Nobuo Nishi2 Author Orcid Image ;   Michihiro Araki2 Author Orcid Image ;   Lei Hum Wee1, 3 Author Orcid Image
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JMIR Formative Res: Predicting Overweight and Obesity Status Among Malaysian Working Adults With Machine Learning o… https://t.co/Bey4nE0paK

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RT @jmirpub: JMIR Formative Res: Predicting Overweight and Obesity Status Among Malaysian Working Adults With Machine Learning or Logistic…

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RT @jmirpub: JMIR Formative Res: Predicting Overweight and Obesity Status Among Malaysian Working Adults With Machine Learning or Logistic…

2:00 AM · Dec 08, 2022

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Jyh Eiin Jyh Eiin @JyhEiin

Very pleased to share my first project which applied machine learning in overweight and obesity prediction. This c… https://t.co/uAbU0iodtd

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