Artificial intelligence-based evaluation of carotid artery compressibility via point-of-care ultrasound in determining the return of spontaneous circulation during cardiopulmonary resuscitation.

Journal: Resuscitation
PMID:

Abstract

AIM: This study introduces RealCAC-Net, an artificial intelligence (AI) system, to quantify carotid artery compressibility (CAC) and determine the return of spontaneous circulation (ROSC) during cardiopulmonary resuscitation.

Authors

  • Subin Park
    Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul 06351, Republic of Korea.
  • Hee Yoon
    Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea, 06351. Electronic address: wildhi.yoon@samsung.com.
  • Soo Yeon Kang
    Department of Emergency Medicine, Chung-ang University Gwangmyeong Hospital, Gwangmyeong-si, Gyeonggi-do, Republic of Korea, 14353.
  • Ik Joon Jo
    Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea, 06351.
  • Sejin Heo
    Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81, Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
  • Hansol Chang
    Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea, 06351.
  • Jong Eun Park
    Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea, 06351.
  • Guntak Lee
    Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea, 06351.
  • Taerim Kim
    Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81, Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
  • Sung Yeon Hwang
    Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea, 06351.
  • Soyoung Park
    Department of Pediatric Dentistry, School of Dentistry, Pusan National University, 50612 Yangsan, Republic of Korea.
  • Myung Jin Chung
    Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 0631, Republic of Korea; Medical AI Research Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul 06351, Republic of Korea. Electronic address: mj1.chung@samsung.com.