Predictive Modeling Using Artificial Intelligence and Machine Learning Algorithms on Electronic Health Record Data : Advantages and Challenges - 11/09/23
, Vincent X. Liu, MD, MS c, ⁎ Résumé |
The rapid adoption of electronic health record (EHR) systems in US hospitals from 2008 to 2014 produced novel data elements for analysis. Concurrent innovations in computing architecture and machine learning (ML) algorithms have made rapid consumption of health data feasible and a powerful engine for clinical innovation. In critical care research, the net convergence of these trends has resulted in an exponential increase in outcome prediction research. In the following article, we explore the history of outcome prediction in the intensive care unit (ICU), the growing use of EHR data, and the rise of artificial intelligence and ML (AI) in critical care.
Le texte complet de cet article est disponible en PDF.Keywords : Critical care outcome prediction, Machine learning, Sepsis prediction, Mortality prediction, Data science, Clinical informatics, Model performance evaluation, Electronic medical record analysis
Plan
Vol 39 - N° 4
P. 647-673 - octobre 2023 Retour au numéro
Article précédent
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