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Published on in Vol 8, No 3 (2022): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39003, first published .
Laptop displaying a diagram on CANCER and Natural Language Processing mining clinical notes.

Exploring the Association of Cancer and Depression in Electronic Health Records: Combining Encoded Diagnosis and Mining Free-Text Clinical Notes

Exploring the Association of Cancer and Depression in Electronic Health Records: Combining Encoded Diagnosis and Mining Free-Text Clinical Notes

Journals

  1. Sim J, Huang X, Horan M, Baker J, Huang I. Using natural language processing to analyze unstructured patient-reported outcomes data derived from electronic health records for cancer populations: a systematic review. Expert Review of Pharmacoeconomics & Outcomes Research 2024;24(4):467 View
  2. Yang Y, Han W, Zhang X, Yuan H, Wang R, Yang J, An C, Huang D. Depression-related innate immune genes and pan-cancer gene analysis and validation. Frontiers in Genetics 2025;15 View
  3. Lin A, Zhang Y, Jiang A, Zhu L, Mou W, Cheng Q, Zhang J, Zhang P, Tang B, Luo P. Integrating digital solutions improves mental health management in cancer care. Communications Medicine 2026;6(1) View
  4. Kayira A, Elyazori H, Lybarger K, Walter F, Chelala C, Funston G. Natural Language Processing of Clinical Notes for Cancer Research and Patient Care Prior to Widespread Adoption of Generative AI: Scoping Review. JMIR AI 2026;5:e73481 View