Published on in Vol 10, No 5 (2022): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35293, first published .
Comparison of Severity of Illness Scores and Artificial Intelligence Models That Are Predictive of Intensive Care Unit Mortality: Meta-analysis and Review of the Literature

Comparison of Severity of Illness Scores and Artificial Intelligence Models That Are Predictive of Intensive Care Unit Mortality: Meta-analysis and Review of the Literature

Comparison of Severity of Illness Scores and Artificial Intelligence Models That Are Predictive of Intensive Care Unit Mortality: Meta-analysis and Review of the Literature

Journals

  1. Rav Acha M, Taha L, Turyan A, Farkash R, Bayya F, Karmi M, Steinmetz Y, Shaheen F, Perel N, Hamayel K, Levi N, Karameh H, Tvito A, Glikson M, Asher E. D-Dimer as a Prognostic Factor in a Tertiary Center Intensive Coronary Care Unit. Clinical and Applied Thrombosis/Hemostasis 2022;28:107602962211108 View
  2. Chander S, Kumari R, Sadarat F, Luhana S. The Evolution and Future of Intensive Care Management in the Era of Telecritical Care and Artificial Intelligence. Current Problems in Cardiology 2023;48(10):101805 View
  3. Flaatten H, Beil M. Predicting ICU Outcomes. CHEST 2023;164(3):570 View
  4. Taylor B, Barboi C, Boustani M. Passive digital markers for Alzheimer's disease and other related dementias: A systematic evidence review. Journal of the American Geriatrics Society 2023;71(9):2966 View
  5. Wehkamp K, Krawczak M, Schreiber S. The quality and utility of artificial intelligence in patient care. Deutsches Ärzteblatt international 2023 View
  6. Moosavi Kashani S, Zargar Balaye Jame S. Mortality Prediction in Emergency Department Using Machine Learning Models. Journal of Archives in Military Medicine 2023;11(3) View
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  8. Chen Y, He J, Wu Q, Pu S, Song C. Prevalence and risk factors of exposure keratopathy among critically ill patients: A systematic review and meta‐analysis. Nursing Open 2024;11(1) View
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  10. Valiente Fernández M, Lesmes González de Aledo A, Martín Badía I, Delgado Moya F. Comparing Traditional Regression and Machine Learning Models in Predicting Acute Respiratory Distress Syndrome Mortality. Critical Care Medicine 2024;52(2):e105 View
  11. Khalifa M, Albadawy M. Artificial Intelligence for Clinical Prediction: Exploring Key Domains and Essential Functions. Computer Methods and Programs in Biomedicine Update 2024;5:100148 View
  12. Kuziemsky C, Chrimes D, Minshall S, Mannerow M, Lau F. AI Quality Standards in Health Care: Rapid Umbrella Review. Journal of Medical Internet Research 2024;26:e54705 View
  13. Ruksakulpiwat S, Thorngthip S, Niyomyart A, Benjasirisan C, Phianhasin L, Aldossary H, Ahmed B, Samai T. A Systematic Review of the Application of Artificial Intelligence in Nursing Care: Where are We, and What’s Next?. Journal of Multidisciplinary Healthcare 2024;Volume 17:1603 View
  14. Beil M, Moreno R, Fronczek J, Kogan Y, Moreno R, Flaatten H, Guidet B, de Lange D, Leaver S, Nachshon A, van Heerden P, Joskowicz L, Sviri S, Jung C, Szczeklik W. Prognosticating the outcome of intensive care in older patients—a narrative review. Annals of Intensive Care 2024;14(1) View