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

Machine Learning (1501) Pulmonology, COPD (145) Clinical Information and Decision Making (1434) Decision Support for Health Professionals (1210) Clinical Informatics (1050)

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

Journals

  1. Liao K, Liu C, Chen C, Shen Y. Machine Learning Approaches for Predicting Acute Respiratory Failure, Ventilator Dependence, and Mortality in Chronic Obstructive Pulmonary Disease. Diagnostics 2021;11(12):2396 View
  2. Kawano K, Otaki Y, Suzuki N, Fujimoto S, Iseki K, Moriyama T, Yamagata K, Tsuruya K, Narita I, Kondo M, Shibagaki Y, Kasahara M, Asahi K, Watanabe T, Konta T. Prediction of mortality risk of health checkup participants using machine learning-based models: the J-SHC study. Scientific Reports 2022;12(1) View
  3. Karthick G, Pankajavalli P. Chronic obstructive pulmonary disease prediction using Internet of things-spiro system and fuzzy-based quantum neural network classifier. Theoretical Computer Science 2023;941:55 View
  4. Suzuki M, Matsumoto I, Ishida M, Horie Y, Ban H, Takeuchi W, Nakagawa S, Nakagawa T, Kitamura T, Muro S. Investigation of time profile of FEV1 across the onset of potential COPD: a retrospective cohort study using medical checkup data in Japan. Scientific Reports 2023;13(1) View
  5. Makimoto K, Hogg J, Bourbeau J, Tan W, Kirby M. CT Imaging With Machine Learning for Predicting Progression to COPD in Individuals at Risk. CHEST 2023;164(5):1139 View
  6. Diaz A. Seeing and Not Seeing Is Believing. CHEST 2023;164(5):1069 View
  7. Xu S, Deo R, Soar J, Barua P, Faust O, Homaira N, Jaffe A, Kabir A, Acharya U. Automated detection of airflow obstructive diseases: A systematic review of the last decade (2013-2022). Computer Methods and Programs in Biomedicine 2023;241:107746 View
  8. Budiarto A, Tsang K, Wilson A, Sheikh A, Shah S. Machine Learning–Based Asthma Attack Prediction Models From Routinely Collected Electronic Health Records: Systematic Scoping Review. JMIR AI 2023;2:e46717 View
  9. Shen X, Liu H. Using machine learning for early detection of chronic obstructive pulmonary disease: a narrative review. Respiratory Research 2024;25(1) View

Books/Policy Documents

  1. Tasmi S, Raihan M, Nasif A, Shams A. Information Technologies and Intelligent Decision Making Systems. View