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

Wearable Devices and Sensors (825) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1317) Ubiquitous Health (uHealth) (117) Machine Learning (1400) Decision Support for Health Professionals (1145) Clinical Information and Decision Making (1339) Pulmonology, COPD (126) Environmental Health (69) Artificial Intelligence (1214) Fitness Trackers and Smart Pedometers/Accelerometers (543)

Published on in Vol 9, No 5 (2021): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22591, first published .
Acute Exacerbation of a Chronic Obstructive Pulmonary Disease Prediction System Using Wearable Device Data, Machine Learning, and Deep Learning: Development and Cohort Study

Acute Exacerbation of a Chronic Obstructive Pulmonary Disease Prediction System Using Wearable Device Data, Machine Learning, and Deep Learning: Development and Cohort Study

Acute Exacerbation of a Chronic Obstructive Pulmonary Disease Prediction System Using Wearable Device Data, Machine Learning, and Deep Learning: Development and Cohort Study

Authors of this article:

Chia-Tung Wu1 Author Orcid Image ;   Guo-Hung Li2 Author Orcid Image ;   Chun-Ta Huang3 Author Orcid Image ;   Yu-Chieh Cheng2 Author Orcid Image ;   Chi-Hsien Chen4 Author Orcid Image ;   Jung-Yien Chien3 Author Orcid Image ;   Ping-Hung Kuo3 Author Orcid Image ;   Lu-Cheng Kuo3 Author Orcid Image ;   Feipei Lai1 Author Orcid Image
Article Authors Cited by (50) Tweetations (6) Metrics

Journals

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  19. ZhuParris A, de Goede A, Yocarini I, Kraaij W, Groeneveld G, Doll R. Machine Learning Techniques for Developing Remotely Monitored Central Nervous System Biomarkers Using Wearable Sensors: A Narrative Literature Review. Sensors 2023;23(11):5243 View
  20. Gálvez-Barrón C, Pérez-López C, Villar-Álvarez F, Ribas J, Formiga F, Chivite D, Boixeda R, Iborra C, Rodríguez-Molinero A. Machine learning for the development of diagnostic models of decompensated heart failure or exacerbation of chronic obstructive pulmonary disease. Scientific Reports 2023;13(1) View
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  24. Jacobson P, Lind L, Persson H. Unleashing the Power of Very Small Data to Predict Acute Exacerbations of Chronic Obstructive Pulmonary Disease. International Journal of Chronic Obstructive Pulmonary Disease 2023;Volume 18:1457 View
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  27. BAGABIR S. Comparison of pulmonary rehabilitation and chest physiotherapy's outcomes among elder patients with chronic obstructive pulmonary disease: a meta-analysis. Minerva Biotechnology and Biomolecular Research 2023;35(2) View
  28. Sami R, Salehi K, Hashemi M, Haghighat S, Atashi V. Barriers to adherence to home-based pulmonary rehabilitation among patients with chronic obstructive pulmonary disease in Iran: a descriptive qualitative study. BMJ Open 2023;13(10):e073972 View
  29. Liu J, Shih C, Huang H, Peng J, Cheng S, Tsai J, Lai F. Evaluating the Potential of Machine Learning and Wearable Devices in End-of-Life Care in Predicting 7-Day Death Events Among Patients With Terminal Cancer: Cohort Study. Journal of Medical Internet Research 2023;25:e47366 View
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Books/Policy Documents

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