Published on in Vol 20, No 9 (2018): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9227, first published .
Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease: Application of Machine Learning to Telemonitoring Data

Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease: Application of Machine Learning to Telemonitoring Data

Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease: Application of Machine Learning to Telemonitoring Data

Journals

  1. Kouri A, Gupta S, Yadollahi A, Ryan C, Gershon A, To T, Tarlo S, Goldstein R, Chapman K, Chow C. Addressing Reduced Laboratory-Based Pulmonary Function Testing During a Pandemic. Chest 2020;158(6):2502 View
  2. Alwashmi M, Fitzpatrick B, Davis E, Farrell J, Gamble J, Hawboldt J. Features of a mobile health intervention to manage chronic obstructive pulmonary disease: a qualitative study. Therapeutic Advances in Respiratory Disease 2020;14:175346662095104 View
  3. Luo G, Stone B, Koebnick C, He S, Au D, Sheng X, Murtaugh M, Sward K, Schatz M, Zeiger R, Davidson G, Nkoy F. Using Temporal Features to Provide Data-Driven Clinical Early Warnings for Chronic Obstructive Pulmonary Disease and Asthma Care Management: Protocol for a Secondary Analysis. JMIR Research Protocols 2019;8(6):e13783 View
  4. Gonem S, Janssens W, Das N, Topalovic M. Applications of artificial intelligence and machine learning in respiratory medicine. Thorax 2020;75(8):695 View
  5. van der Kleij R, Kasteleyn M, Meijer E, Bonten T, Houwink E, Teichert M, van Luenen S, Vedanthan R, Evers A, Car J, Pinnock H, Chavannes N. SERIES: eHealth in primary care. Part 1: Concepts, conditions and challenges. European Journal of General Practice 2019;25(4):179 View
  6. Mlodzinski E, Stone D, Celi L. Machine Learning for Pulmonary and Critical Care Medicine: A Narrative Review. Pulmonary Therapy 2020;6(1):67 View
  7. Li X, Xie Y, Zhao H, Zhang H, Yu X, Li J. Telemonitoring Interventions in COPD Patients: Overview of Systematic Reviews. BioMed Research International 2020;2020:1 View
  8. Bull L, Lunt M, Martin G, Hyrich K, Sergeant J. Harnessing repeated measurements of predictor variables for clinical risk prediction: a review of existing methods. Diagnostic and Prognostic Research 2020;4(1) View
  9. Bugajski A, Lengerich A, Koerner R, Szalacha L. Utilizing an Artificial Neural Network to Predict Self‐Management in Patients With Chronic Obstructive Pulmonary Disease: An Exploratory Analysis. Journal of Nursing Scholarship 2021;53(1):16 View
  10. Luo G, Stone B, Sheng X, He S, Koebnick C, Nkoy F. Using Computational Methods to Improve Integrated Disease Management for Asthma and Chronic Obstructive Pulmonary Disease: Protocol for a Secondary Analysis. JMIR Research Protocols 2021;10(5):e27065 View
  11. Giri P, Chowdhury A, Bedoya A, Chen H, Lee H, Lee P, Henriquez C, MacIntyre N, Huang Y. Application of Machine Learning in Pulmonary Function Assessment Where Are We Now and Where Are We Going?. Frontiers in Physiology 2021;12 View
  12. Pegoraro J, Lavault S, Wattiez N, Similowski T, Gonzalez-Bermejo J, Birmelé E. Machine-learning based feature selection for a non-invasive breathing change detection. BioData Mining 2021;14(1) View
  13. Zeng S, Arjomandi M, Luo G. Automatically Explaining Machine Learning Predictions on Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study. JMIR Medical Informatics 2022;10(2):e33043 View
  14. Althobiani M, Evans R, Alqahtani J, Aldhahir A, Russell A, Hurst J, Porter J. Home monitoring of physiology and symptoms to detect interstitial lung disease exacerbations and progression: a systematic review. ERJ Open Research 2021;7(4):00441-2021 View
  15. Ródenas-Rigla F, Conesa D, López-Quílez A, Durá-Ferrandis E. A Classification System for Decision-Making in the Management of Patients with Chronic Conditions. Sustainability 2021;13(23):13176 View
  16. 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
  17. Zeng S, Arjomandi M, Tong Y, Liao Z, Luo G. Developing a Machine Learning Model to Predict Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study. Journal of Medical Internet Research 2022;24(1):e28953 View
  18. Wang K, Gu L, Liu W, Xu C, Yin C, Liu H, Rong L, Li W, Wei X. The predictors of death within 1 year in acute ischemic stroke patients based on machine learning. Frontiers in Neurology 2023;14 View
  19. Pinnock H, Hui C, van Boven J. Implementation of digital home monitoring and management of respiratory disease. Current Opinion in Pulmonary Medicine 2023;29(4):302 View
  20. Cascarano A, Mur-Petit J, Hernández-González J, Camacho M, de Toro Eadie N, Gkontra P, Chadeau-Hyam M, Vitrià J, Lekadir K. Machine and deep learning for longitudinal biomedical data: a review of methods and applications. Artificial Intelligence Review 2023;56(S2):1711 View
  21. 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
  22. Coutu F, Iorio O, Ross B. Remote patient monitoring strategies and wearable technology in chronic obstructive pulmonary disease. Frontiers in Medicine 2023;10 View
  23. Glyde H, Blythin A, Wilkinson T, Nabney I, Dodd J. Exacerbation predictive modelling using real-world data from the myCOPD app. Heliyon 2024;10(10):e31201 View
  24. Khirani S, Patout M, Arnal J. Telemonitoring in Non-invasive Ventilation. Sleep Medicine Clinics 2024 View
  25. Anderson E, Lennon M, Kavanagh K, Weir N, Kernaghan D, Roper M, Dunlop E, Lapp L. Predictive Data Analytics in Telecare and Telehealth: A Systematic Scoping Review (Preprint). Online Journal of Public Health Informatics 2024 View
  26. Esposito P, Antonucci G, Palozzi G, Fijałkowska J. Cognitive systems for improving decision-making in the workplace: an explorative study within the waste management field. Management Decision 2024 View
  27. Glyde H, Morgan C, Wilkinson T, Nabney I, Dodd J. Remote patient monitoring and machine learning in acute exacerbations of COPD: A dual systematic literature review and narrative synthesis (Preprint). Journal of Medical Internet Research 2023 View

Books/Policy Documents

  1. do Amaral J, de Melo P. Artificial Intelligence in Precision Health. View
  2. Das N, Topalovic M, Janssens W. Artificial Intelligence in Medicine. View
  3. Das N, Topalovic M, Janssens W. Artificial Intelligence in Medicine. View
  4. Kasten J. Research Anthology on Big Data Analytics, Architectures, and Applications. View
  5. Lucangeli L, D’Angelantonio E, D’Abbondanza N, Ferrazza M, Piuzzi E, Camomilla V, Pallotti A. Social Innovation in Long-Term Care Through Digitalization. View
  6. Gonem S. Artificial Intelligence in Clinical Practice. View