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Citing this Article

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Published on 15.11.18 in Vol 20, No 11 (2018): November

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

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

According to Crossref, the following articles are citing this article (DOI 10.2196/12001):

(note that this is only a small subset of citations)

  1. Burns JW, Gerhart J, Rizvydeen M, Kimura M, Burgess HJ. Morning Bright Light Treatment for Chronic Low Back Pain: Potential Impact on the Volatility of Pain, Mood, Function, and Sleep. Pain Medicine 2020;21(6):1153
  2. Moore RJ, Smith R, Liu Q. Using computational ethnography to enhance the curation of real-world data (RWD) for chronic pain and invisible disability use cases. ACM SIGACCESS Accessibility and Computing 2020;(127):1
  3. Necka EA, Lee I, Kucyi A, Cheng JC, Yu Q, Atlas LY. Applications of dynamic functional connectivity to pain and its modulation. PAIN Reports 2019;4(4):e752
  4. Simpao AF, Rehman MA. Anesthesia Informatics in 2018. Advances in Anesthesia 2019;37:145
  5. Rahman QA, Janmohamed T, Clarke H, Ritvo P, Heffernan J, Katz J. Interpretability and Class Imbalance in Prediction Models for Pain Volatility in Manage My Pain App Users: Analysis Using Feature Selection and Majority Voting Methods. JMIR Medical Informatics 2019;7(4):e15601