{"title":"临床实践中的人工智能:质量与证据。","authors":"R Puchades, L Ramos-Ruperto","doi":"10.1016/j.rceng.2024.11.001","DOIUrl":null,"url":null,"abstract":"<p><p>A revolution is taking place within the field of artificial intelligence (AI) with the emergence of generative AI. Although we are in an early phase at the clinical level, there is an exponential increase in the number of scientific articles that use AI (discriminative and generative) in their methodology. According to the current situation, we may be in an \"AI bubble\" stage; requiring filters and tools to evaluate its application, based on the quality and evidence provided. In this sense, initiatives have been developed to determine standards and guidelines for the use of discriminative AI (CONSORT AI, STARD AI and others), and more recently for generative AI (the CHART collaborative). As a new technology, AI requires scientific regulation to guarantee the efficacy and safety of its applications, while maintaining the quality of care; an evidence-based AI (IABE).</p>","PeriodicalId":94354,"journal":{"name":"Revista clinica espanola","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence in clinical practice: Quality and evidence.\",\"authors\":\"R Puchades, L Ramos-Ruperto\",\"doi\":\"10.1016/j.rceng.2024.11.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>A revolution is taking place within the field of artificial intelligence (AI) with the emergence of generative AI. Although we are in an early phase at the clinical level, there is an exponential increase in the number of scientific articles that use AI (discriminative and generative) in their methodology. According to the current situation, we may be in an \\\"AI bubble\\\" stage; requiring filters and tools to evaluate its application, based on the quality and evidence provided. In this sense, initiatives have been developed to determine standards and guidelines for the use of discriminative AI (CONSORT AI, STARD AI and others), and more recently for generative AI (the CHART collaborative). As a new technology, AI requires scientific regulation to guarantee the efficacy and safety of its applications, while maintaining the quality of care; an evidence-based AI (IABE).</p>\",\"PeriodicalId\":94354,\"journal\":{\"name\":\"Revista clinica espanola\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Revista clinica espanola\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.rceng.2024.11.001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista clinica espanola","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.rceng.2024.11.001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Artificial intelligence in clinical practice: Quality and evidence.
A revolution is taking place within the field of artificial intelligence (AI) with the emergence of generative AI. Although we are in an early phase at the clinical level, there is an exponential increase in the number of scientific articles that use AI (discriminative and generative) in their methodology. According to the current situation, we may be in an "AI bubble" stage; requiring filters and tools to evaluate its application, based on the quality and evidence provided. In this sense, initiatives have been developed to determine standards and guidelines for the use of discriminative AI (CONSORT AI, STARD AI and others), and more recently for generative AI (the CHART collaborative). As a new technology, AI requires scientific regulation to guarantee the efficacy and safety of its applications, while maintaining the quality of care; an evidence-based AI (IABE).