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

Theme Issue 2021: Health Natural Language Processing and Applications (16) Machine Learning (1401) Consumer & Patient Education and Shared-Decision Making (641) Artificial Intelligence (1216)

Published on in Vol 9, No 5 (2021): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28413, first published .
Use of Machine Learning Algorithms to Predict the Understandability of Health Education Materials: Development and Evaluation Study

Use of Machine Learning Algorithms to Predict the Understandability of Health Education Materials: Development and Evaluation Study

Use of Machine Learning Algorithms to Predict the Understandability of Health Education Materials: Development and Evaluation Study

Authors of this article:

Meng Ji1 Author Orcid Image ;   Yanmeng Liu1 Author Orcid Image ;   Mengdan Zhao1 Author Orcid Image ;   Ziqing Lyu1, 2 Author Orcid Image ;   Boren Zhang1 Author Orcid Image ;   Xin Luo3, 4 Author Orcid Image ;   Yanlin Li3, 4 Author Orcid Image ;   Yin Zhong5, 6 Author Orcid Image
Article Authors Cited by (5) Tweetations (1) Metrics

Journals

  1. Ji M, Bouillon P. Predicting the Linguistic Accessibility of Chinese Health Translations: Machine Learning Algorithm Development. JMIR Medical Informatics 2021;9(10):e30588 View
  2. Shi J, Babar M. Deep Learning for College English Education Evaluation. Mobile Information Systems 2022;2022:1 View
  3. Xie W, Ji C, Hao T, Chow C. Predicting the Easiness and Complexity of English Health Materials for International Tertiary Students With Linguistically Enhanced Machine Learning Algorithms: Development and Validation Study. JMIR Medical Informatics 2021;9(10):e25110 View
  4. Ayre J, Bonner C, Muscat D, Dunn A, Harrison E, Dalmazzo J, Mouwad D, Aslani P, Shepherd H, McCaffery K. Multiple Automated Health Literacy Assessments of Written Health Information: Development of the SHeLL (Sydney Health Literacy Lab) Health Literacy Editor v1. JMIR Formative Research 2023;7:e40645 View
  5. Ayre J, Muscat D, Mac O, Bonner C, Dunn A, Dalmazzo J, Mouwad D, McCaffery K. Helping patient educators meet health literacy needs: End-user testing and iterative development of an innovative health literacy editing tool. PEC Innovation 2023;2:100162 View