Artificial intelligence (AI) versus expert: A comparison of left ventricular outflow tract velocity time integral (LVOT-VTI) assessment between ICU doctors and an AI tool.

Journal: Journal of applied clinical medical physics
Published Date: Aug 1, 2022

Abstract

PURPOSE: The application of point of care ultrasound (PoCUS) in medical education is a relatively new course. There are still great differences in the existence, quantity, provision, and depth of bedside ultrasound education. The left ventricular outflow tract velocity time integral (LVOT-VTI) has been successfully used in several studies as a parameter for hemodynamic management of critically ill patients, especially in the evaluation of fluid responsiveness. While LVOT-VTI has been broadly used, valuable applications using artificial intelligence (AI) in PoCUS is still limited. We aimed to identify the degree of correlation between auto LVOT-VTI and the manual LVOT-VTI acquired by PoCUS trained ICU doctors.

Authors

  • Shanshan Zhai
    Department of Surgery Intensive Care Unit, China-Japan Friendship Hospital, Beijing, China.
  • Hui Wang
    Department of Vascular Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
  • Lichao Sun
    School of Education, Communication & Society, King's College London, London SE5 9RJ, UK.
  • Bo Zhang
    Department of Clinical Pharmacology, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310006, PR China.
  • Feng Huo
    Department of Emergency Medicine, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China.
  • Shuang Qiu
    College of Food Science and Nutritional Engineering, China Agricultural University, P.O. Box 40, No. 17 Qinghua East Road, Haidian District Beijing, 100083 People's Republic China.
  • Xiaoqing Wu
    Department of Surgery Intensive Care Unit, China-Japan Friendship Hospital, Beijing, China.
  • Junyu Ma
    Department of Surgery Intensive Care Unit, China-Japan Friendship Hospital, Beijing, China.
  • Yina Wu
    Department of Surgery Intensive Care Unit, China-Japan Friendship Hospital, Beijing, China.
  • Jun Duan
    Department of Surgery Intensive Care Unit, China-Japan Friendship Hospital, Beijing, China.

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