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Natural Language Processing (976) Electronic Health Records (1400)

Published on in Vol 4, No 4 (2016): Oct-Dec

Finding Important Terms for Patients in Their Electronic Health Records: A Learning-to-Rank Approach Using Expert Annotations

Finding Important Terms for Patients in Their Electronic Health Records: A Learning-to-Rank Approach Using Expert Annotations

Finding Important Terms for Patients in Their Electronic Health Records: A Learning-to-Rank Approach Using Expert Annotations

Authors of this article:

Jinying Chen1 Author Orcid Image ;   Jiaping Zheng2 Author Orcid Image ;   Hong Yu1, 3 Author Orcid Image
Article Authors Cited by (9) Tweetations (1) Metrics

Journals

  1. Chen J, Jagannatha A, Fodeh S, Yu H. Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach. JMIR Medical Informatics 2017;5(4):e42 View
  2. Chen J, Lalor J, Liu W, Druhl E, Granillo E, Vimalananda V, Yu H. Detecting Hypoglycemia Incidents Reported in Patients’ Secure Messages: Using Cost-Sensitive Learning and Oversampling to Reduce Data Imbalance. Journal of Medical Internet Research 2019;21(3):e11990 View
  3. Qassimi S, Abdelwahed E. The role of collaborative tagging and ontologies in emerging semantic of web resources. Computing 2019;101(10):1489 View
  4. Chen J, Yu H. Unsupervised ensemble ranking of terms in electronic health record notes based on their importance to patients. Journal of Biomedical Informatics 2017;68:121 View
  5. Kersloot M, van Putten F, Abu-Hanna A, Cornet R, Arts D. Natural language processing algorithms for mapping clinical text fragments onto ontology concepts: a systematic review and recommendations for future studies. Journal of Biomedical Semantics 2020;11(1) View
  6. Tenorio J, de Moraes F, Pisa I. CHV.br: Exploratory study for the development of a consumer health vocabulary (CHV) supported by a network model for Brazilian Portuguese language. Journal of Information Science 2025;51(3):556 View
  7. Jang W, Sultana S, Yao Z, Tran H, Yang Z, Kwon S, Yu H. Enhancing LLMs for Identifying and Prioritizing Important Medical Jargons from Electronic Health Record Notes Utilizing Data Augmentation: A Comparative Study (Preprint). JMIR AI 2025 View

Books/Policy Documents

  1. He Z. Social Web and Health Research. View

Conference Proceedings

  1. van den Bercken L, Sips R, Lofi C. The World Wide Web Conference on - WWW '19. Evaluating Neural Text Simplification in the Medical Domain View