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

Machine Learning (1465) Pulmonology, COPD (143) Clinical Information and Decision Making (1407) Decision Support for Health Professionals (1185) Clinical Informatics (1022)

Published on in Vol 9, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24796, first published .
Machine Learning Methods for the Diagnosis of Chronic Obstructive Pulmonary Disease in Healthy Subjects: Retrospective Observational Cohort Study

Machine Learning Methods for the Diagnosis of Chronic Obstructive Pulmonary Disease in Healthy Subjects: Retrospective Observational Cohort Study

Machine Learning Methods for the Diagnosis of Chronic Obstructive Pulmonary Disease in Healthy Subjects: Retrospective Observational Cohort Study

Authors of this article:

Shigeo Muro1 Author Orcid Image ;   Masato Ishida2 Author Orcid Image ;   Yoshiharu Horie3 Author Orcid Image ;   Wataru Takeuchi4 Author Orcid Image ;   Shunki Nakagawa4 Author Orcid Image ;   Hideyuki Ban4 Author Orcid Image ;   Tohru Nakagawa5 Author Orcid Image ;   Tetsuhisa Kitamura6 Author Orcid Image
Article Authors Cited by (12) Tweetations (8) Metrics

Shigeo Muro   1 , MD, PhD ;   Masato Ishida   2 , MSc ;   Yoshiharu Horie   3 , PhD ;   Wataru Takeuchi   4 , MEng ;   Shunki Nakagawa   4 , MSc ;   Hideyuki Ban   4 , PhD ;   Tohru Nakagawa   5 , MD, PhD ;   Tetsuhisa Kitamura   6 , MD, MSc, DPH

1 Department of Respiratory Medicine, Nara Medical University, Nara, Japan

2 Department of Respiratory and Immunology, Medical, AstraZeneca KK, Osaka, Japan

3 Department of Data Science, Medical, AstraZeneca KK, Osaka, Japan

4 Center for Technology Innovation–Artificial Intelligence, Research & Development Group, Hitachi, Ltd, Tokyo, Japan

5 Hitachi Health Care Center, Hitachi, Ltd, Ibaraki, Japan

6 Division of Environmental Medicine and Population Sciences, Department of Social and Environmental Medicine, Graduate School of Medicine, Osaka University, Osaka, Japan

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