Published on in Vol 26 (2024)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/62890, first published
.
Journals
- Antra , Kumar U, Loria G, Nayak Y. Beyond the alarm: proactive predictions for cardiac arrest incidents in hospitals using Interpretable machine learning models. Journal of the Operational Research Society 2024:1 View
- Sang W, Ma J, Zhang X, Wu S, Pan C, Zheng J, Zheng W, Yuan Q, Zhang J, Ma J, Xu F. Early prediction cardiac arrest in intensive care units: the value of laboratory indicator trends. World Journal of Emergency Medicine 2025;16(1):67 View
- Tang H, Qu M, Xin M, He T, Al-Nimer M. Association of mean corpuscular volume with 28-day mortality in sepsis patients: A retrospective cohort study using eICU data. PLOS ONE 2025;20(4):e0321213 View
- Al-Ansari A, Nejad F, Al-Nasr R, Prithula J, Rahman T, Hasan A, Chowdhury M, Alam M. Predicting ICU Mortality Among Septic Patients Using Machine Learning Technique. Journal of Clinical Medicine 2025;14(10):3495 View
- Li Y, Xiao M, Li Y, Lv L, Zhang S, Liu Y, Zhang J. Machine Learning for the Prediction of Acute Kidney Injury in Critically Ill Patients With Coronary Heart Disease: Algorithm Development and Validation. JMIR Medical Informatics 2025;13:e72349 View
Books/Policy Documents
- Mekata Y, Kishigami A, Hamaguchi J, Nakanishi M. Engineering Psychology and Cognitive Ergonomics. View