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

Lemos ATN;
Silva EL;
Silva JVL;
Damasio J;
Correia FF;
Calixto GC;
Freire TSP;
de Morais RBAR;
Araújo KES;
Ribeiro YC;
de Oliveira ES;
dos Anjos AQ;
Franco EB;
Teixeira LS;
Hildefonso DM

Atinelle Teles Novais Lemos

Elton Lemos Silva

João Victor Lemos Silva

Joyce Damasio

Felipe Freire Correia

Gabriela Chaves Calixto

Tainá Sales Prudêncio Freire

Rian Barreto Arrais Rodrigues de Morais

Karoline Eyshila Sousa Araújo

Yohanna Candido Ribeiro

Emanuelle Santos de Oliveira

Abraão Queiroz dos Anjos

Edielma Batista Franco

Lucas da Silva Teixeira

Diogo Mariano Hildefonso


Keywords

Artificial intelligence
Intensive Care Unit
Machine Learning
Monitoring
Personalized treatment

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.

 

DOI:https://doi.org/10.56238/sevened2024.031-059


Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Copyright (c) 2024 Atinelle Teles Novais Lemos, Elton Lemos Silva, João Victor Lemos Silva, Joyce Damasio , Felipe Freire Correia, Gabriela Chaves Calixto, Tainá Sales Prudêncio Freire, Rian Barreto Arrais Rodrigues de Morais, Karoline Eyshila Sousa Araújo, Yohanna Candido Ribeiro, Emanuelle Santos de Oliveira , Abraão Queiroz dos Anjos, Edielma Batista Franco, Lucas da Silva Teixeira, Diogo Mariano Hildefonso

Author(s)

  • Atinelle Teles Novais Lemos
  • Elton Lemos Silva
  • João Victor Lemos Silva
  • Joyce Damasio
  • Felipe Freire Correia
  • Gabriela Chaves Calixto
  • Tainá Sales Prudêncio Freire
  • Rian Barreto Arrais Rodrigues de Morais
  • Karoline Eyshila Sousa Araújo
  • Yohanna Candido Ribeiro
  • Emanuelle Santos de Oliveira
  • Abraão Queiroz dos Anjos
  • Edielma Batista Franco
  • Lucas da Silva Teixeira
  • Diogo Mariano Hildefonso