Deep-Learning-Based Survival Prediction of Patients in Coronary Care Units.

Journal: Computational and mathematical methods in medicine
Published Date: Dec 24, 2021

Abstract

BACKGROUND: A survival prediction model based on deep learning has higher accuracy than the CPH model in predicting the survival of CCU patients, and it also has a better discrimination ability. We collected information on patients with various diseases in coronary care units (CCUs) from the Medical Information Mart for Intensive Care III (MIMIC-III) database. The purpose of this study was to use this information to construct a neural-network model based on deep learning to predict the survival probabilities of patients with conditions that are common in CCUs.

Authors

  • Rui Yang
    Department of Biomedical Informatics, Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore.
  • Tao Huang
    The Second Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, China.
  • Zichen Wang
    Department of Pharmacology and Systems Therapeutics, Department of Genetics and Genomic Sciences, BD2K-LINCS Data Coordination and Integration Center (DCIC), Mount Sinai's Knowledge Management Center for Illuminating the Druggable Genome (KMC-IDG), Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Wei Huang
    Shaanxi Institute of Flexible Electronics, Northwestern Polytechnical University, 710072 Xi'an, China.
  • Aozi Feng
    Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510630, China.
  • Li Li
    Department of Gastric Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China.
  • Jun Lyu
    Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.

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