A machine learning stacking model accurately estimating gastric fluid volume in patients undergoing elective sedated gastrointestinal endoscopy.

Journal: Postgraduate medicine
Published Date: Mar 22, 2024

Abstract

BACKGROUND: The current point-of-care ultrasound (POCUS) assessment of gastric fluid volume primarily relies on the traditional linear approach, which often suffers from moderate accuracy. This study aimed to develop an advanced machine learning (ML) model to estimate gastric fluid volume more accurately.

Authors

  • Yuqing Yan
    School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.
  • Yuzhan Jin
    School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.
  • Yaoyi Guo
    Department of Anesthesiology, Perioperative and Pain Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
  • Mingtao Ma
    Department of Anesthesiology, Perioperative and Pain Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
  • Yue Feng
    Nursing School, Sichuan University, China.
  • Yi Zhong
    Department of Chinese Medicine Science & Engineering,Zhejiang University Hangzhou 310058,China.
  • Chen Chen
    The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
  • Chun Ge
    Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
  • Jianjun Zou
    School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China; Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
  • Yanna Si
    Department of Anesthesiology, Perioperative and Pain Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.

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