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Machine Learning and Health Science Research: Tutorial.

Hunyong ChoJane SheDaniel De MarchiHelal El-ZaatariEdward L BarnesAngelica Cristello SarteauMichael R KosorokArti V Virkud
Published in: Journal of medical Internet research (2024)
Machine learning (ML) has seen impressive growth in health science research due to its capacity for handling complex data to perform a range of tasks, including unsupervised learning, supervised learning, and reinforcement learning. To aid health science researchers in understanding the strengths and limitations of ML and to facilitate its integration into their studies, we present here a guideline for integrating ML into an analysis through a structured framework, covering steps from framing a research question to study design and analysis techniques for specialized data types.
Keyphrases
  • machine learning
  • public health
  • big data
  • healthcare
  • mental health
  • artificial intelligence
  • health information
  • electronic health record
  • health promotion
  • working memory
  • deep learning
  • climate change