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Machine Learning Model for Anesthetic Risk Stratification for Gynecologic and Obstetric Patients: Cross-Sectional Study Outlining a Novel Approach for Early Detection.

Feng-Fang TsaiYung-Chun ChangYu-Wen ChiuBor-Ching SheuMin-Huei HsuHuei-Ming Yeh
Published in: JMIR formative research (2024)
Research Ethics Committee of the National Taiwan University Hospital 202204010RINB; https://www.ntuh.gov.tw/RECO/Index.action.
Keyphrases
  • machine learning
  • end stage renal disease
  • ejection fraction
  • newly diagnosed
  • chronic kidney disease
  • pregnant women
  • public health
  • big data
  • artificial intelligence
  • quality improvement
  • patient reported