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

Natural Language Processing (706) Ontologies, Classifications, and Coding (243) Linguistics, Comprehension, and Learning (53)

Published on in Vol 5, No 4 (2017): Oct-Dec

Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach

Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach

Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach

Authors of this article:

Jinying Chen1 Author Orcid Image ;   Abhyuday N Jagannatha2 Author Orcid Image ;   Samah J Fodeh3 Author Orcid Image ;   Hong Yu1, 4 Author Orcid Image
Article Authors Cited by (16) Tweetations (6) Metrics

Journals

  1. Chen J, Druhl E, Polepalli Ramesh B, Houston T, Brandt C, Zulman D, Vimalananda V, Malkani S, Yu H. A Natural Language Processing System That Links Medical Terms in Electronic Health Record Notes to Lay Definitions: System Development Using Physician Reviews. Journal of Medical Internet Research 2018;20(1):e26 View
  2. Wang Y, Sohn S, Liu S, Shen F, Wang L, Atkinson E, Amin S, Liu H. A clinical text classification paradigm using weak supervision and deep representation. BMC Medical Informatics and Decision Making 2019;19(1) View
  3. Uribe-Toril J, Ruiz-Real J, Nievas-Soriano B. A Study of eHealth from the Perspective of Social Sciences. Healthcare 2021;9(2):108 View
  4. Choudhury A, Elkefi S, Strachna O, Asan O. Effect of patient portals on perception of care quality, general health, and mental health: An exploratory analysis. Human Factors in Healthcare 2022;2:100018 View
  5. van Mens H, Martens S, Paiman E, Mertens A, Nienhuis R, de Keizer N, Cornet R. Diagnosis clarification by generalization to patient-friendly terms and definitions: Validation study. Journal of Biomedical Informatics 2022;129:104071 View
  6. Li X, Zhang Y, Jin J, Sun F, Li N, Liang S, Ijaz M. A model of integrating convolution and BiGRU dual-channel mechanism for Chinese medical text classifications. PLOS ONE 2023;18(3):e0282824 View
  7. Lalor J, Levy D, Jordan H, Hu W, Smirnova J, Yu H. Evaluating Expert-Layperson Agreement in Identifying Jargon Terms in Electronic Health Record Notes: Observational Study. Journal of Medical Internet Research 2024;26:e49704 View
  8. Levy D, Jordan H, Lalor J, Smirnova J, Hu W, Liu W, Yu H. Individual factors that affect laypeople's understanding of definitions of medical jargon. Health Policy and Technology 2024;13(6):100932 View

Books/Policy Documents

  1. He Z. Social Web and Health Research. View
  2. Hamed A, Leszczynska A, Schreiber M. The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2019). View
  3. Abdeen Hamed A, Leszczynska A, Schoenberg M, Temesi G, Verspoor K. Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges. View