Contribution of Artificial Intelligence in the early detection of patients at risk of cardiac arrest in a hospital context

• DOI: 10.22533/at.ed.1592592201108

• Palavras-chave: artificial intelligence, cardiac arrest and early diagnosis.

• Keywords: artificial intelligence, cardiac arrest and early diagnosis.

• Abstract:

  Background: Artificial Intelligence (AI) tools have been analyzed and tested in hospital healthcare to early detect the risk of the patient going into Cardio-Respiratory Arrest (CPA).

  Goals: To describe the scientific evidence on the contribution of AI in the early detection of patients at risk of CRA in a hospital context and to reflect on the importance of using AI tools in hospital practice.

  Methodology: An integrative literature review was carried out. Data collection was performed from June to July 2021, in PubMed, ScienceDirect, BMC and Medline databases, with the equation “Artificial Intelligence AND Heart Arrest AND Early Diagnosis”.

  Results: Of the 162 articles obtained by the search, 6 articles were selected after applying the inclusion criteria: Of these, 5 quantitative, retrospective cohort studies and 1 case study, which involved a total of 88592 patients.

  Conclusion: The AI algorithms identified are more sensitive for the early detection of patients at risk of CRA compared to conventional methods already existing in hospital settings. AI tools have the potential to assist and assist healthcare professionals during clinical practice in decision making.