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

Methods and Instruments in Medical Informatics (104) Electronic Health Records (966) Machine Learning (1385) Natural Language Processing (644) Back Pain (103)

Published on in Vol 8, No 2 (2020): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16878, first published .
Identifying Acute Low Back Pain Episodes in Primary Care Practice From Clinical Notes: Observational Study

Identifying Acute Low Back Pain Episodes in Primary Care Practice From Clinical Notes: Observational Study

Identifying Acute Low Back Pain Episodes in Primary Care Practice From Clinical Notes: Observational Study

Authors of this article:

Riccardo Miotto1, 2, 3 Author Orcid Image ;   Bethany L Percha2, 3 Author Orcid Image ;   Benjamin S Glicksberg1, 2, 3 Author Orcid Image ;   Hao-Chih Lee2, 3 Author Orcid Image ;   Lisanne Cruz4 Author Orcid Image ;   Joel T Dudley2, 3 Author Orcid Image ;   Ismail Nabeel5 Author Orcid Image
Article Authors Cited by (16) Tweetations (16) Metrics

Journals

  1. Percha B. Modern Clinical Text Mining: A Guide and Review. Annual Review of Biomedical Data Science 2021;4(1):165 View
  2. Lu H, Ehwerhemuepha L, Rakovski C. A comparative study on deep learning models for text classification of unstructured medical notes with various levels of class imbalance. BMC Medical Research Methodology 2022;22(1) View
  3. Al-hihi E, Gibson C, Lee J, Mount R, Irani N, McGowan C. Improving appropriate imaging for non-specific low back pain. BMJ Open Quality 2022;11(1):e001539 View
  4. Jujjavarapu C, Pejaver V, Cohen T, Mooney S, Heagerty P, Jarvik J. A Comparison of Natural Language Processing Methods for the Classification of Lumbar Spine Imaging Findings Related to Lower Back Pain. Academic Radiology 2022;29:S188 View
  5. Kim Y, Song C, Song G, Kim S, Han H, Han I. Using Natural Language Processing to Identify Low Back Pain in Imaging Reports. Applied Sciences 2022;12(24):12521 View
  6. D’Antoni F, Russo F, Ambrosio L, Bacco L, Vollero L, Vadalà G, Merone M, Papalia R, Denaro V. Artificial Intelligence and Computer Aided Diagnosis in Chronic Low Back Pain: A Systematic Review. International Journal of Environmental Research and Public Health 2022;19(10):5971 View
  7. Bousquet C, Coulet A. Supporting Diagnosis With Next-Generation Artificial Intelligence. JAMA 2022;327(14):1400 View
  8. Bacco L, Russo F, Ambrosio L, D’Antoni F, Vollero L, Vadalà G, Dell’Orletta F, Merone M, Papalia R, Denaro V. Natural language processing in low back pain and spine diseases: A systematic review. Frontiers in Surgery 2022;9 View
  9. Badreau M, Fadel M, Roquelaure Y, Bertin M, Rapicault C, Gilbert F, Porro B, Descatha A. Comparison of Machine Learning Methods in the Study of Cancer Survivors’ Return to Work: An Example of Breast Cancer Survivors with Work-Related Factors in the CONSTANCES Cohort. Journal of Occupational Rehabilitation 2023;33(4):750 View
  10. Vaid A, Landi I, Nadkarni G, Nabeel I. Using fine-tuned large language models to parse clinical notes in musculoskeletal pain disorders. The Lancet Digital Health 2023;5(12):e855 View
  11. Jaiswal A, Katz A, Nesca M, Milios E. Identifying Risk Factors Associated With Lower Back Pain in Electronic Medical Record Free Text: Deep Learning Approach Using Clinical Note Annotations. JMIR Medical Informatics 2023;11:e45105 View
  12. Cascella M, Schiavo D, Cuomo A, Ottaiano A, Perri F, Patrone R, Migliarelli S, Bignami E, Vittori A, Cutugno F, Hu L. Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives. Pain Research and Management 2023;2023:1 View
  13. Meier T, Refahi M, Hearne G, Restifo D, Munoz-Acuna R, Rosen G, Woloszynek S. The Role and Applications of Artificial Intelligence in the Treatment of Chronic Pain. Current Pain and Headache Reports 2024 View

Books/Policy Documents

  1. De Freitas J, Glicksberg B, Johnson K, Miotto R. Machine Learning in Cardiovascular Medicine. View
  2. Singh M, Sharma A. Artificial Intelligence Trends in Systems. View
  3. Shah R, Reese V, Oselkin M, P. Stawicki S. Artificial Intelligence in Medicine and Surgery - An Exploration of Current Trends, Potential Opportunities, and Evolving Threats - Volume 1. View