USE OF AI IN THE ICU FOR MONITORING CRITICALLY ILL PATIENTS: A LITERATURE REVIEW

Abstract

INTRODUCTION: The advancement of artificial intelligence (AI) has revolutionized the management of critically ill patients, especially in Intensive Care Units (ICUs). Through predictive algorithms, AI enables real-time analysis of large volumes of data, helping to identify serious conditions early and personalize treatments. This has provided faster diagnoses and more accurate interventions, in addition to optimizing clinical decision-making. OBJECTIVE: With this in mind, the objective of this study was to analyze the impact of the main artificial intelligences for the optimization of intensive care. METHODOLOGY: The present work is an integrative literature review, in view of the need to agglutinate the main types of scientific works and analyze their impact related to the theme under discussion. The search was carried out in an exploratory manner in the main databases of the medical literature, such as PubMED, Cochrane, SciELO and Web of Science. RESULTS: The results obtained reinforce the importance of the use of artificial intelligence (AI) in monitoring, early diagnosis, and personalization of care in ICUs. Several studies highlight the positive impacts of AI, particularly in the continuous monitoring of vital signs and the early detection of critical conditions such as sepsis, organ failure, and other complications in critically ill patients. CONCLUSION: The use of AI in intensive care medicine has already demonstrated its value in improving clinical outcomes, reducing mortality, and personalizing the treatment of critically ill patients, as long as it continues to be implemented as a clinical decision support and not as a substitute for medical judgment.