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Using natural language processing for identification of herpes zoster ophthalmicus cases to support population-based study.

Chengyi ZhengYi LuoCheryl MercadoLina SySteven J JacobsenBrad AckersonBruno LewinHung Fu Tseng
Published in: Clinical & experimental ophthalmology (2018)
We developed and validated an automatic method to identify HZO cases with high accuracy. As one of the largest studies on HZO, our finding emphasizes the importance of preventing HZ in the elderly population. This method can be a valuable tool to support population-based studies and clinical care of HZO in the era of big data.
Keyphrases
  • big data
  • machine learning
  • artificial intelligence
  • case control
  • healthcare
  • deep learning
  • palliative care
  • autism spectrum disorder
  • quality improvement
  • pain management
  • community dwelling
  • chronic pain