Published on in Vol 10, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28934, first published .
Evaluation of the Need for Intensive Care in Children With Pneumonia: Machine Learning Approach

Evaluation of the Need for Intensive Care in Children With Pneumonia: Machine Learning Approach

Evaluation of the Need for Intensive Care in Children With Pneumonia: Machine Learning Approach

Journals

  1. Gottlieb E, Samuel M, Bonventre J, Celi L, Mattie H. Machine Learning for Acute Kidney Injury Prediction in the Intensive Care Unit. Advances in Chronic Kidney Disease 2022;29(5):431 View
  2. Gawronski O, Latour J, Cecchetti C, Iula A, Ravà L, Ciofi degli Atti M, Dall’Oglio I, Tiozzo E, Raponi M, Parshuram C. Escalation of care in children at high risk of clinical deterioration in a tertiary care children’s hospital using the Bedside Pediatric Early Warning System. BMC Pediatrics 2022;22(1) View
  3. Chang T, Liu Y, Lin S, Chiu P, Chou C, Chang L, Lai F. Clinical characteristics of hospitalized children with community-acquired pneumonia and respiratory infections: Using machine learning approaches to support pathogen prediction at admission. Journal of Microbiology, Immunology and Infection 2023;56(4):772 View
  4. Lin S, Wu J, Liu Y, Chiu P, Chang T, Wu E, Chou C, Chang L, Lai F. Machine learning models to evaluate mortality in pediatric patients with pneumonia in the intensive care unit. Pediatric Pulmonology 2024;59(5):1256 View