{"title":"人工智能在危重病人安全中的应用现状。","authors":"Jesús Abelardo Barea Mendoza, Marcos Valiente Fernandez, Alex Pardo Fernandez, Josep Gómez Álvarez","doi":"10.1016/j.medine.2024.04.002","DOIUrl":null,"url":null,"abstract":"<p><p>Intensive Care Units (ICUs) have undergone enhancements in patient safety, and artificial intelligence (AI) emerges as a disruptive technology offering novel opportunities. While the published evidence is limited and presents methodological issues, certain areas show promise, such as decision support systems, detection of adverse events, and prescription error identification. The application of AI in safety may pursue predictive or diagnostic objectives. Implementing AI-based systems necessitates procedures to ensure secure assistance, addressing challenges including trust in such systems, biases, data quality, scalability, and ethical and confidentiality considerations. The development and application of AI demand thorough testing, encompassing retrospective data assessments, real-time validation with prospective cohorts, and efficacy demonstration in clinical trials. Algorithmic transparency and explainability are essential, with active involvement of clinical professionals being crucial in the implementation process.</p>","PeriodicalId":49268,"journal":{"name":"Medicina Intensiva","volume":" ","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Current perspectives on the use of artificial intelligence in critical patient safety.\",\"authors\":\"Jesús Abelardo Barea Mendoza, Marcos Valiente Fernandez, Alex Pardo Fernandez, Josep Gómez Álvarez\",\"doi\":\"10.1016/j.medine.2024.04.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Intensive Care Units (ICUs) have undergone enhancements in patient safety, and artificial intelligence (AI) emerges as a disruptive technology offering novel opportunities. While the published evidence is limited and presents methodological issues, certain areas show promise, such as decision support systems, detection of adverse events, and prescription error identification. The application of AI in safety may pursue predictive or diagnostic objectives. Implementing AI-based systems necessitates procedures to ensure secure assistance, addressing challenges including trust in such systems, biases, data quality, scalability, and ethical and confidentiality considerations. The development and application of AI demand thorough testing, encompassing retrospective data assessments, real-time validation with prospective cohorts, and efficacy demonstration in clinical trials. Algorithmic transparency and explainability are essential, with active involvement of clinical professionals being crucial in the implementation process.</p>\",\"PeriodicalId\":49268,\"journal\":{\"name\":\"Medicina Intensiva\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-04-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Medicina Intensiva\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.medine.2024.04.002\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CRITICAL CARE MEDICINE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medicina Intensiva","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.medine.2024.04.002","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CRITICAL CARE MEDICINE","Score":null,"Total":0}
Current perspectives on the use of artificial intelligence in critical patient safety.
Intensive Care Units (ICUs) have undergone enhancements in patient safety, and artificial intelligence (AI) emerges as a disruptive technology offering novel opportunities. While the published evidence is limited and presents methodological issues, certain areas show promise, such as decision support systems, detection of adverse events, and prescription error identification. The application of AI in safety may pursue predictive or diagnostic objectives. Implementing AI-based systems necessitates procedures to ensure secure assistance, addressing challenges including trust in such systems, biases, data quality, scalability, and ethical and confidentiality considerations. The development and application of AI demand thorough testing, encompassing retrospective data assessments, real-time validation with prospective cohorts, and efficacy demonstration in clinical trials. Algorithmic transparency and explainability are essential, with active involvement of clinical professionals being crucial in the implementation process.
期刊介绍:
Medicina Intensiva is the journal of the Spanish Society of Intensive Care Medicine and Coronary Units (SEMICYUC) and of Pan American and Iberian Federation of Societies of Intensive and Critical Care Medicine. Medicina Intensiva has become the reference publication in Spanish in its field. The journal mainly publishes Original Articles, Reviews, Clinical Notes, Consensus Documents, Images, and other information relevant to the specialty. All works go through a rigorous selection process. The journal accepts submissions of articles in English and in Spanish languages. The journal follows the publication requirements of the International Committee of Medical Journal Editors (ICMJE) and the Committee on Publication Ethics (COPE).