Machine learning methods for developing a predictive model of the incidence of delirium in cardiac intensive care units.

Journal: Revista espanola de cardiologia (English ed.)
PMID: 38237663

Abstract

INTRODUCTION AND OBJECTIVES: Delirium, recognized as a crucial prognostic factor in the cardiac intensive care unit (CICU), has evolved in response to the changing demographics among critically ill cardiac patients. This study aimed to create a predictive model for delirium for patients in the CICU.

Authors

  • Ryoung-Eun Ko
    Department of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Jihye Lee
    Department of Digital Media, Ajou University, 206, World cup-ro, Yeongtong-gu, Suwon-si, Gyeonggi-do, Republic of Korea.
  • Sungeun Kim
    Radiology & Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
  • Joong Hyun Ahn
    Biostatics and Clinical Epidemiology Center, Samsung Medical Center, Seoul, Republic of Korea.
  • Soo Jin Na
    Department of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Jeong Hoon Yang
    Department of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea; Division of Cardiology, Department of Medicine, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. Electronic address: jhysmc@gmail.com.

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