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

Mobile Health (mhealth) (2939) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1399)

Published on in Vol 20, No 11 (2018): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12001, first published .
Defining and Predicting Pain Volatility in Users of the Manage My Pain App: Analysis Using Data Mining and Machine Learning Methods

Defining and Predicting Pain Volatility in Users of the Manage My Pain App: Analysis Using Data Mining and Machine Learning Methods

Defining and Predicting Pain Volatility in Users of the Manage My Pain App: Analysis Using Data Mining and Machine Learning Methods

Authors of this article:

Quazi Abidur Rahman1 Author Orcid Image ;   Tahir Janmohamed2 Author Orcid Image ;   Meysam Pirbaglou3 Author Orcid Image ;   Hance Clarke4 Author Orcid Image ;   Paul Ritvo3, 5 Author Orcid Image ;   Jane M Heffernan1 Author Orcid Image ;   Joel Katz3, 4, 5 Author Orcid Image
Article Authors Cited by (28) Tweetations (6) Metrics

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  10. Schwab J, Schobel J, Werle S, Furstberger A, Ikonomi N, Szekely R, Thiam P, Huhne R, Jahn N, Schuler R, Kuhn P, Holderried M, Steger F, Reichert M, Kaisers U, Kestler A, Seufferlein T, Kestler H. Perspective on mHealth Concepts to Ensure Users’ Empowerment–From Adverse Event Tracking for COVID-19 Vaccinations to Oncological Treatment. IEEE Access 2021;9:83863 View
  11. Gerner M, Vuillerme N, Aubourg T, Messner E, Terhorst Y, Hörmann V, Ganzleben I, Schenker H, Schett G, Atreya R, Neurath M, Knitza J, Orlemann T. Review and Analysis of German Mobile Apps for Inflammatory Bowel Disease Management Using the Mobile Application Rating Scale: Systematic Search in App Stores and Content Analysis. JMIR mHealth and uHealth 2022;10(5):e31102 View
  12. Verma D, Bach K, Mork P. Application of Machine Learning Methods on Patient Reported Outcome Measurements for Predicting Outcomes: A Literature Review. Informatics 2021;8(3):56 View
  13. Su D, Li Q, Zhang T, Veliz P, Chen Y, He K, Mahajan P, Zhang X. Prediction of acute appendicitis among patients with undifferentiated abdominal pain at emergency department. BMC Medical Research Methodology 2022;22(1) View
  14. Verma D, Jansen D, Bach K, Poel M, Mork P, d’Hollosy W. Exploratory application of machine learning methods on patient reported data in the development of supervised models for predicting outcomes. BMC Medical Informatics and Decision Making 2022;22(1) View
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  16. Zhang P, Jiang Y, Liu G, Han J, Wang J, Ma L, Hu W, Zhang J. Altered brain functional network dynamics in classic trigeminal neuralgia: a resting-state functional magnetic resonance imaging study. The Journal of Headache and Pain 2021;22(1) View
  17. Xu G, Tang W, Zhou C, Xu J, Cheng C, Gong W, Dong S, Zhang Y. Pain Fluctuations of Women with Subacute Herpetic Neuralgia During Local Methylcobalamin in Combination with Lidocaine Treatment: A Single-Blinded Randomized Controlled Trial. Journal of Pain Research 2023;Volume 16:1267 View
  18. Koh R, Khan M, Rashidiani S, Hassan S, Tucci V, Liu T, Nesovic K, Kumbhare D, Doyle T. Check It Before You Wreck It: A Guide to STAR-ML for Screening Machine Learning Reporting in Research. IEEE Access 2023;11:101567 View
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  20. Khan M, Koh R, Rashidiani S, Liu T, Tucci V, Kumbhare D, Doyle T. Cracking the Chronic Pain code: A scoping review of Artificial Intelligence in Chronic Pain research. Artificial Intelligence in Medicine 2024;151:102849 View
  21. Wu H, Chen Z, Gu J, Jiang Y, Gao S, Chen W, Miao C. Predicting Chronic Pain and Treatment Outcomes Using Machine Learning Models Based on High-dimensional Clinical Data From a Large Retrospective Cohort. Clinical Therapeutics 2024;46(6):490 View
  22. Little C, Schultz D, House T, Dixon W, McBeth J. Identifying Weekly Trajectories of Pain Severity Using Daily Data From an mHealth Study: Cluster Analysis. JMIR mHealth and uHealth 2024;12:e48582 View
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Books/Policy Documents

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