Published on in Vol 23, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28361, first published .
Developing a Time-Adaptive Prediction Model for Out-of-Hospital Cardiac Arrest: Nationwide Cohort Study in Korea

Developing a Time-Adaptive Prediction Model for Out-of-Hospital Cardiac Arrest: Nationwide Cohort Study in Korea

Developing a Time-Adaptive Prediction Model for Out-of-Hospital Cardiac Arrest: Nationwide Cohort Study in Korea

Journals

  1. Spadafora L, Biondi-Zoccai G, Bernardi M. Out-of-hospital cardiac arrest: predict and then protect!. eBioMedicine 2023;90:104517 View
  2. Yoo K, Cho Y, Oh J, Lee J, Ko B, Kang H, Lim T, Lee S. Association of Socioeconomic Status With Long-Term Outcome in Survivors After Out-of-Hospital Cardiac Arrest: Nationwide Population-Based Longitudinal Study. JMIR Public Health and Surveillance 2023;9:e47156 View
  3. Toy J, Bosson N, Schlesinger S, Gausche-Hill M, Stratton S. Artificial intelligence to support out-of-hospital cardiac arrest care: A scoping review. Resuscitation Plus 2023;16:100491 View
  4. Chang H, Kim J, Jung W, Heo S, Lee S, Kim T, Hwang S, Do Shin S, Cha W, Ong M. Machine learning pre-hospital real-time cardiac arrest outcome prediction (PReCAP) using time-adaptive cohort model based on the Pan-Asian Resuscitation Outcome Study. Scientific Reports 2023;13(1) View
  5. Zobeiri A, Rezaee A, Hajati F, Argha A, Alinejad-Rokny H. Post-Cardiac arrest outcome prediction using machine learning: A systematic review and meta-analysis. International Journal of Medical Informatics 2025;193:105659 View