Published on in Vol 10, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37658, first published .
Predicting Abnormalities in Laboratory Values of Patients in the Intensive Care Unit Using Different Deep Learning Models: Comparative Study

Predicting Abnormalities in Laboratory Values of Patients in the Intensive Care Unit Using Different Deep Learning Models: Comparative Study

Predicting Abnormalities in Laboratory Values of Patients in the Intensive Care Unit Using Different Deep Learning Models: Comparative Study

Journals

  1. Chen J, Stumpe M, Cohen E. Evolving From Discrete Molecular Data Integrations to Actionable Molecular Insights Within the Electronic Health Record. JCO Clinical Cancer Informatics 2024;(8) View
  2. Bashiri F, Carey K, Martin J, Koyner J, Edelson D, Gilbert E, Mayampurath A, Afshar M, Churpek M. Development and external validation of deep learning clinical prediction models using variable-length time series data. Journal of the American Medical Informatics Association 2024;31(6):1322 View
  3. Primavesi F, Senoner T, Schindler S, Nikolajevic A, Di Fazio P, Csukovich G, Eller S, Neumayer B, Anliker M, Braunwarth E, Oberhuber R, Resch T, Maglione M, Cardini B, Niederwieser T, Gasteiger S, Klieser E, Tilg H, Schneeberger S, Neureiter D, Öfner D, Troppmair J, Stättner S. The Interplay between Perioperative Oxidative Stress and Hepatic Dysfunction after Human Liver Resection: A Prospective Observational Pilot Study. Antioxidants 2024;13(5):590 View
  4. Ayad A, Tai Y, Dartmann G, Schmeink A. Smart Summary: A Distributed Medical Recommender System for Patients in the ICU Using Neural Networks. IEEE Access 2024;12:83719 View