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TECHNOLOGY THAT CARES: THE IMPACT OF ARTIFICIAL INTELLIGENCE ON EMERGENCY MEDICINE

This study addresses the application of Artificial Intelligence (AI) in emergency care, an area of health characterized by the approach and need for quick and accurate decisions, representing a transformative opportunity for process optimization and improvement of clinical care. AI has emerged as a tool with the potential to optimize triage, predict risks and support clinical decision-making in complex scenarios. This is an integrative, qualitative, retrospective and cross-sectional literature review, which analyzed scientific articles from the PubMed and Virtual Health Library databases, published between 2020 and 2025, obtaining a total of 12 articles for analysis. The review explores the transformative potential of AI in optimization, prediction and support tasks. It highlights studies that prove its effectiveness in screening patients, tracking conditions such as cognitive impairment, predicting mortality from sepsis and personalizing treatments for conditions such as heart failure. These applications demonstrate the technology's ability to process complex data to improve the efficiency of care. However, the success of AI depends crucially on its correct integration and human supervision, in which its analyses are validated by the clinical judgment of a professional, guaranteeing the safety and quality of care.

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TECHNOLOGY THAT CARES: THE IMPACT OF ARTIFICIAL INTELLIGENCE ON EMERGENCY MEDICINE

  • DOI: https://doi.org/10.22533/at.ed.1595262514074

  • Palavras-chave: Artificial Intelligence; Emergency; Decision.

  • Keywords: Artificial Intelligence; Emergency; Decision.

  • Abstract:

    This study addresses the application of Artificial Intelligence (AI) in emergency care, an area of health characterized by the approach and need for quick and accurate decisions, representing a transformative opportunity for process optimization and improvement of clinical care. AI has emerged as a tool with the potential to optimize triage, predict risks and support clinical decision-making in complex scenarios. This is an integrative, qualitative, retrospective and cross-sectional literature review, which analyzed scientific articles from the PubMed and Virtual Health Library databases, published between 2020 and 2025, obtaining a total of 12 articles for analysis. The review explores the transformative potential of AI in optimization, prediction and support tasks. It highlights studies that prove its effectiveness in screening patients, tracking conditions such as cognitive impairment, predicting mortality from sepsis and personalizing treatments for conditions such as heart failure. These applications demonstrate the technology's ability to process complex data to improve the efficiency of care. However, the success of AI depends crucially on its correct integration and human supervision, in which its analyses are validated by the clinical judgment of a professional, guaranteeing the safety and quality of care.

  • Alana de Freitas e Silva
  • Alan Autran Lamego
  • Ana Luiza de Rezende
  • Camila Farenzena Raubach
  • Camila Repsold Vieira
  • João Gabriel Mello de Almeida
  • Júlia Carvalho Cunha
  • Melissa Lin Tong
  • Paula Castro Tofani
  • Samuel Ferreira França Filho
  • Tomás Tejerina Sellos Costa Bahia de Almeida
  • Ramon Fraga de Souza Lima
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