{"title":"人工智能的前景:回顾人工智能在医疗保健领域的机遇和挑战。","authors":"Yuri Y M Aung, David C S Wong, Daniel S W Ting","doi":"10.1093/bmb/ldab016","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields in various sectors, including healthcare. This article reviews AI's present applications in healthcare, including its benefits, limitations and future scope.</p><p><strong>Sources of data: </strong>A review of the English literature was conducted with search terms 'AI' or 'ML' or 'deep learning' and 'healthcare' or 'medicine' using PubMED and Google Scholar from 2000-2021.</p><p><strong>Areas of agreement: </strong>AI could transform physician workflow and patient care through its applications, from assisting physicians and replacing administrative tasks to augmenting medical knowledge.</p><p><strong>Areas of controversy: </strong>From challenges training ML systems to unclear accountability, AI's implementation is difficult and incremental at best. Physicians also lack understanding of what AI implementation could represent.</p><p><strong>Growing points: </strong>AI can ultimately prove beneficial in healthcare, but requires meticulous governance similar to the governance of physician conduct.</p><p><strong>Areas timely for developing research: </strong>Regulatory guidelines are needed on how to safely implement and assess AI technology, alongside further research into the specific capabilities and limitations of its medical use.</p>","PeriodicalId":9280,"journal":{"name":"British medical bulletin","volume":"139 1","pages":"4-15"},"PeriodicalIF":6.7000,"publicationDate":"2021-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"70","resultStr":"{\"title\":\"The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare.\",\"authors\":\"Yuri Y M Aung, David C S Wong, Daniel S W Ting\",\"doi\":\"10.1093/bmb/ldab016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields in various sectors, including healthcare. This article reviews AI's present applications in healthcare, including its benefits, limitations and future scope.</p><p><strong>Sources of data: </strong>A review of the English literature was conducted with search terms 'AI' or 'ML' or 'deep learning' and 'healthcare' or 'medicine' using PubMED and Google Scholar from 2000-2021.</p><p><strong>Areas of agreement: </strong>AI could transform physician workflow and patient care through its applications, from assisting physicians and replacing administrative tasks to augmenting medical knowledge.</p><p><strong>Areas of controversy: </strong>From challenges training ML systems to unclear accountability, AI's implementation is difficult and incremental at best. Physicians also lack understanding of what AI implementation could represent.</p><p><strong>Growing points: </strong>AI can ultimately prove beneficial in healthcare, but requires meticulous governance similar to the governance of physician conduct.</p><p><strong>Areas timely for developing research: </strong>Regulatory guidelines are needed on how to safely implement and assess AI technology, alongside further research into the specific capabilities and limitations of its medical use.</p>\",\"PeriodicalId\":9280,\"journal\":{\"name\":\"British medical bulletin\",\"volume\":\"139 1\",\"pages\":\"4-15\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2021-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"70\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"British medical bulletin\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/bmb/ldab016\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"British medical bulletin","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/bmb/ldab016","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare.
Introduction: Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields in various sectors, including healthcare. This article reviews AI's present applications in healthcare, including its benefits, limitations and future scope.
Sources of data: A review of the English literature was conducted with search terms 'AI' or 'ML' or 'deep learning' and 'healthcare' or 'medicine' using PubMED and Google Scholar from 2000-2021.
Areas of agreement: AI could transform physician workflow and patient care through its applications, from assisting physicians and replacing administrative tasks to augmenting medical knowledge.
Areas of controversy: From challenges training ML systems to unclear accountability, AI's implementation is difficult and incremental at best. Physicians also lack understanding of what AI implementation could represent.
Growing points: AI can ultimately prove beneficial in healthcare, but requires meticulous governance similar to the governance of physician conduct.
Areas timely for developing research: Regulatory guidelines are needed on how to safely implement and assess AI technology, alongside further research into the specific capabilities and limitations of its medical use.
期刊介绍：
British Medical Bulletin is a multidisciplinary publication, which comprises high quality reviews aimed at generalist physicians, junior doctors, and medical students in both developed and developing countries.
Its key aims are to provide interpretations of growing points in medicine by trusted experts in the field, and to assist practitioners in incorporating not just evidence but new conceptual ways of thinking into their practice.
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