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

Christine JiYanmeng LiuMengdan ZhaoZiqing LyuBoren ZhangXin LuoYanlin LiYin Zhong
Published in: JMIR medical informatics (2021)
Machine learning algorithms were developed to predict health information understandability for international college students aged 25-30 years. Thirteen natural language features and 5 evaluation dimensions were identified and compared in terms of their impact on the performance of the models. Health information understandability varies according to the demographic profiles of the target readers, and for international tertiary students, improving health information evidentness, relevance, and logic is critical.
Keyphrases
  • health information
  • machine learning
  • social media
  • healthcare
  • artificial intelligence
  • big data
  • deep learning
  • autism spectrum disorder
  • public health
  • mental health
  • clinical evaluation