Artificial Intelligence in Cardiac Critical Care: Current Insights and Future Prospects

Abstract

Cardiac critical care (CCC) involves a heterogenous group of critically ill patients and poses an ever-growing challenge to the healthcare system. Moreover, their clinical outcome improved to an unprecedented level due to significant improvements in the critical care practice. Artificial intelligence (AI) is an emerging transdisciplinary field that involves multidomain and multidimensional computerized data to handle heterogeneity, complexity, and acuity which were the major limitations of conventional critical care practice. AI employs machine learning techniques for disease identification from an exhaustive list of differential diagnoses, prediction of disease evolution and its diverse manifestations, dynamic risk calculation, optimal sequential decision-making solutions, and trajected prediction of clinical deterioration or recovery. This review highlights the current advances and implementations of AI algorithms in CCC practice with respect to sepsis, heart failure, arrhythmia, and various cardiovascular diseases.

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