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Question answering systems for health professionals at the point of care-a systematic review.

Gregory KellAngus RobertsSerge UmanskyLinglong QianDavide FerrariFrank SoboczenskiByron C WallaceNikhil PatelIain James Marshall
Published in: Journal of the American Medical Informatics Association : JAMIA (2024)
While machine learning methods have led to increased accuracy, most studies imperfectly reflected real-world healthcare information needs. Key research priorities include developing more realistic healthcare QA datasets and considering the reliability of answer sources, rather than merely focusing on accuracy.
Keyphrases
  • healthcare
  • machine learning
  • health information
  • drinking water
  • artificial intelligence
  • rna seq
  • case control
  • deep learning
  • social media
  • health insurance