{"title":"人工智能:未来 10 年,人工智能将在哪些方面改变心脏病学。","authors":"Sam Brown","doi":"10.5837/bjc.2024.015","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) will revolutionise cardiology practices over the next decade, from optimising diagnostics to individualising treatment strategies. Moreover, it can play an important role in combating gender inequalities in cardiovascular disease outcomes. There is growing evidence that AI algorithms can match humans at echocardiography analysis, while also being able to extract subtle differences that the human eye cannot detect. Similar promise is evident in the analysis of electrocardiograms, creating a new layer of interpretation. From big data, AI can produce algorithms that individualise cardiac risk factors and prevent perpetuating gender biases in diagnosis. Nonetheless, AI implementation requires caution. To avoid worsening health inequalities, it must be trained across diverse populations, and when errors arise, a robust regulatory framework must be in place to ensure safety and accountability. AI is perfectly positioned to capitalise on the growth of big data, but to proceed we require a generation of physicians who understand its fundamentals.</p>","PeriodicalId":74959,"journal":{"name":"The British journal of cardiology","volume":"31 2","pages":"015"},"PeriodicalIF":0.0000,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11562571/pdf/","citationCount":"0","resultStr":"{\"title\":\"Heartificial intelligence: in what ways will artificial intelligence lead to changes in cardiology over the next 10 years.\",\"authors\":\"Sam Brown\",\"doi\":\"10.5837/bjc.2024.015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Artificial intelligence (AI) will revolutionise cardiology practices over the next decade, from optimising diagnostics to individualising treatment strategies. Moreover, it can play an important role in combating gender inequalities in cardiovascular disease outcomes. There is growing evidence that AI algorithms can match humans at echocardiography analysis, while also being able to extract subtle differences that the human eye cannot detect. Similar promise is evident in the analysis of electrocardiograms, creating a new layer of interpretation. From big data, AI can produce algorithms that individualise cardiac risk factors and prevent perpetuating gender biases in diagnosis. Nonetheless, AI implementation requires caution. To avoid worsening health inequalities, it must be trained across diverse populations, and when errors arise, a robust regulatory framework must be in place to ensure safety and accountability. AI is perfectly positioned to capitalise on the growth of big data, but to proceed we require a generation of physicians who understand its fundamentals.</p>\",\"PeriodicalId\":74959,\"journal\":{\"name\":\"The British journal of cardiology\",\"volume\":\"31 2\",\"pages\":\"015\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11562571/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The British journal of cardiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5837/bjc.2024.015\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The British journal of cardiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5837/bjc.2024.015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
Heartificial intelligence: in what ways will artificial intelligence lead to changes in cardiology over the next 10 years.
Artificial intelligence (AI) will revolutionise cardiology practices over the next decade, from optimising diagnostics to individualising treatment strategies. Moreover, it can play an important role in combating gender inequalities in cardiovascular disease outcomes. There is growing evidence that AI algorithms can match humans at echocardiography analysis, while also being able to extract subtle differences that the human eye cannot detect. Similar promise is evident in the analysis of electrocardiograms, creating a new layer of interpretation. From big data, AI can produce algorithms that individualise cardiac risk factors and prevent perpetuating gender biases in diagnosis. Nonetheless, AI implementation requires caution. To avoid worsening health inequalities, it must be trained across diverse populations, and when errors arise, a robust regulatory framework must be in place to ensure safety and accountability. AI is perfectly positioned to capitalise on the growth of big data, but to proceed we require a generation of physicians who understand its fundamentals.