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

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. De Ramón Fernández A, Ruiz Fernández D, Gilart Iglesias V, Marcos Jorquera D. Analyzing the use of artificial intelligence for the management of chronic obstructive pulmonary disease (COPD). International Journal of Medical Informatics 2022;158:104640 View
  3. Zazo-Manzaneque R, Pons-Beltrán V, Vidaurre A, Santonja A, Sánchez-Díaz C. Classification Predictive Model for Air Leak Detection in Endoworm Enteroscopy System. Sensors 2022;22(14):5211 View
  4. Park Y, Go T, Hong S, Kim S, Han J, Kang Y, Kang D. Digital Biomarkers in Living Labs for Vulnerable and Susceptible Individuals: An Integrative Literature Review. Yonsei Medical Journal 2022;63(Suppl):S43 View
  5. Makimoto K, Au R, Moslemi A, Hogg J, Bourbeau J, Tan W, Kirby M. Comparison of Feature Selection Methods and Machine Learning Classifiers for Predicting Chronic Obstructive Pulmonary Disease Using Texture-Based CT Lung Radiomic Features. Academic Radiology 2023;30(5):900 View
  6. Park Y, Lee C, Jung J. Digital Healthcare for Airway Diseases from Personal Environmental Exposure. Yonsei Medical Journal 2022;63(Suppl):S1 View
  7. Pinnock H, Murphie P, Vogiatzis I, Poberezhets V. Telemedicine and virtual respiratory care in the era of COVID-19. ERJ Open Research 2022;8(3):00111-2022 View
  8. Alvarado E, Grágeda N, Luzanto A, Mahu R, Wuth J, Mendoza L, Yoma N. Dyspnea Severity Assessment Based on Vocalization Behavior with Deep Learning on the Telephone. Sensors 2023;23(5):2441 View
  9. Watson A, Wilkinson T. Digital healthcare in COPD management: a narrative review on the advantages, pitfalls, and need for further research. Therapeutic Advances in Respiratory Disease 2022;16:175346662210754 View
  10. Guo S, Akman C. Logistic Regression Analysis of Clinical Characteristics for Differentiation of Chronic Obstructive Pulmonary Disease Severity. Emergency Medicine International 2023;2023:1 View
  11. Fu Y, Kang N, Yu Y, Mi Y, Guo J, Wu J, Weng C. Polyphenols, flavonoids and inflammasomes: the role of cigarette smoke in COPD. European Respiratory Review 2022;31(164):220028 View
  12. Takano A, Ono K, Nozawa K, Sato M, Onuki M, Sese J, Yumoto Y, Matsushita S, Matsumoto T. Wearable Sensor and Mobile App–Based mHealth Approach for Investigating Substance Use and Related Factors in Daily Life: Protocol for an Ecological Momentary Assessment Study. JMIR Research Protocols 2023;12:e44275 View
  13. Zhang B, Wang J, Chen J, Ling Z, Ren Y, Xiong D, Guo L. Machine learning in chronic obstructive pulmonary disease. Chinese Medical Journal 2023;136(5):536 View
  14. Pépin J, Degano B, Tamisier R, Viglino D. Remote Monitoring for Prediction and Management of Acute Exacerbations in Chronic Obstructive Pulmonary Disease (AECOPD). Life 2022;12(4):499 View
  15. Neumann D, Tiberius V, Biendarra F. Adopting wearables to customize health insurance contributions: a ranking-type Delphi. BMC Medical Informatics and Decision Making 2022;22(1) View
  16. Xie Y, Lu L, Gao F, He S, Zhao H, Fang Y, Yang J, An Y, Ye Z, Dong Z. Integration of Artificial Intelligence, Blockchain, and Wearable Technology for Chronic Disease Management: A New Paradigm in Smart Healthcare. Current Medical Science 2021;41(6):1123 View
  17. Mozumder M, Armand T, Imtiyaj Uddin S, Athar A, Sumon R, Hussain A, Kim H. Metaverse for Digital Anti-Aging Healthcare: An Overview of Potential Use Cases Based on Artificial Intelligence, Blockchain, IoT Technologies, Its Challenges, and Future Directions. Applied Sciences 2023;13(8):5127 View
  18. Wieben A, Walden R, Alreshidi B, Brown S, Cato K, Coviak C, Cruz C, D'Agostino F, Douthit B, Forbes T, Gao G, Johnson S, Lee M, Mullen-Fortino M, Park J, Park S, Pruinelli L, Reger A, Role J, Sileo M, Schultz M, Vyas P, Jeffery A. Data Science Implementation Trends in Nursing Practice: A Review of the 2021 Literature. Applied Clinical Informatics 2023;14(03):585 View
  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
  21. Althobiani M, Khan B, Shah A, Ranjan Y, Mendes R, Folarin A, Mandal S, Porter J, Hurst J. Clinicians’ Perspectives of Wearable Technology to Detect and Monitor Exacerbations of Chronic Obstructive Pulmonary Disease: Mixed-Method Survey. International Journal of Chronic Obstructive Pulmonary Disease 2023;Volume 18:1401 View
  22. Zhang J, Chen F, Wang Y, Chen Y. Early detection and prediction of acute exacerbation of chronic obstructive pulmonary disease. Chinese Medical Journal Pulmonary and Critical Care Medicine 2023;1(2):102 View
  23. Wang X, Qiao Y, Cui Y, Ren H, Zhao Y, Linghu L, Ren J, Zhao Z, Chen L, Qiu L. An explainable artificial intelligence framework for risk prediction of COPD in smokers. BMC Public Health 2023;23(1) View
  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
  25. Jacobson P, Lind L, Persson H. The Exacerbation of Chronic Obstructive Pulmonary Disease: Which Symptom is Most Important to Monitor?. International Journal of Chronic Obstructive Pulmonary Disease 2023;Volume 18:1533 View
  26. Coutu F, Iorio O, Ross B. Remote patient monitoring strategies and wearable technology in chronic obstructive pulmonary disease. Frontiers in Medicine 2023;10 View
  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
  30. Liao X, Wu Y, Jiang N, Sun J, Xu W, Gao S, Wang J, Li T, Wang K, Li Q. Automated detection of abnormal respiratory sound from electronic stethoscope and mobile phone using MobileNetV2. Biocybernetics and Biomedical Engineering 2023;43(4):763 View
  31. Shah A, Althobiani M, Saigal A, Ogbonnaya C, Hurst J, Mandal S. Wearable technology interventions in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis. npj Digital Medicine 2023;6(1) View
  32. Gálvez-Barrón C, Pérez-López C. Sistemas diagnósticos de exacerbación de la EPOC en la población anciana: presente y futuro. Open Respiratory Archives 2024;6(1):100291 View
  33. Kurian V, Gee M, Farrington S, Yang E, Okossi A, Chen L, Beris A. Systems Engineering Approach to Modeling and Analysis of Chronic Obstructive Pulmonary Disease Part II: Extension for Variable Metabolic Rates. ACS Omega 2024;9(1):494 View
  34. Vitacca M, Malovini A, Paneroni M, Spanevello A, Ceriana P, Capelli A, Murgia R, Ambrosino N. Predicting Response to In-Hospital Pulmonary Rehabilitation in Individuals Recovering From Exacerbations of Chronic Obstructive Pulmonary Disease. Archivos de Bronconeumología 2024 View
  35. 张 欢. Research Progress of Risk Factors andAntibiotic Therapy in Elderly Patients with AECOPD. Asian Case Reports in Emergency Medicine 2024;12(01):8 View

Books/Policy Documents

  1. Dhaliwal M, Sharma R, Bindra N. Machine Learning, Image Processing, Network Security and Data Sciences. View
  2. Cai Y, Li J, Fan L, Jiang J. LISS 2021. View
  3. Latif T, Dieffenderfer J, da Silva R, Lobaton E, Bozkurt A. Encyclopedia of Sensors and Biosensors. View
  4. Kabir R, Syed H, Vinnakota D, Sivasubramanian M, Hitch G, Okello S, Sharon-Shivuli-Isigi , Pulikkottil A, Mahmud I, Dehghani L, Parsa A. Deep Learning in Personalized Healthcare and Decision Support. View
  5. Cano I, Arismendi E, Borrat X. Digital Respiratory Healthcare. View
  6. Tran L, Thi H, Chu D. Advances in Bioinformatics. View