{"title":"大语言模型在初级保健中的潜在应用和影响。","authors":"Albert Andrew","doi":"10.1136/fmch-2023-002602","DOIUrl":null,"url":null,"abstract":"<p><p>The recent release of highly advanced generative artificial intelligence (AI) chatbots, including ChatGPT and Bard, which are powered by large language models (LLMs), has attracted growing mainstream interest over its diverse applications in clinical practice, including in health and healthcare. The potential applications of LLM-based programmes in the medical field range from assisting medical practitioners in improving their clinical decision-making and streamlining administrative paperwork to empowering patients to take charge of their own health. However, despite the broad range of benefits, the use of such AI tools also comes with several limitations and ethical concerns that warrant further consideration, encompassing issues related to privacy, data bias, and the accuracy and reliability of information generated by AI. The focus of prior research has primarily centred on the broad applications of LLMs in medicine. To the author's knowledge, this is, the first article that consolidates current and pertinent literature on LLMs to examine its potential in primary care. The objectives of this paper are not only to summarise the potential benefits, risks and challenges of using LLMs in primary care, but also to offer insights into considerations that primary care clinicians should take into account when deciding to adopt and integrate such technologies into their clinical practice.</p>","PeriodicalId":44590,"journal":{"name":"Family Medicine and Community Health","volume":"12 Suppl 1","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10828839/pdf/","citationCount":"0","resultStr":"{\"title\":\"Potential applications and implications of large language models in primary care.\",\"authors\":\"Albert Andrew\",\"doi\":\"10.1136/fmch-2023-002602\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The recent release of highly advanced generative artificial intelligence (AI) chatbots, including ChatGPT and Bard, which are powered by large language models (LLMs), has attracted growing mainstream interest over its diverse applications in clinical practice, including in health and healthcare. The potential applications of LLM-based programmes in the medical field range from assisting medical practitioners in improving their clinical decision-making and streamlining administrative paperwork to empowering patients to take charge of their own health. However, despite the broad range of benefits, the use of such AI tools also comes with several limitations and ethical concerns that warrant further consideration, encompassing issues related to privacy, data bias, and the accuracy and reliability of information generated by AI. The focus of prior research has primarily centred on the broad applications of LLMs in medicine. To the author's knowledge, this is, the first article that consolidates current and pertinent literature on LLMs to examine its potential in primary care. The objectives of this paper are not only to summarise the potential benefits, risks and challenges of using LLMs in primary care, but also to offer insights into considerations that primary care clinicians should take into account when deciding to adopt and integrate such technologies into their clinical practice.</p>\",\"PeriodicalId\":44590,\"journal\":{\"name\":\"Family Medicine and Community Health\",\"volume\":\"12 Suppl 1\",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-01-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10828839/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Family Medicine and Community Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1136/fmch-2023-002602\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PRIMARY HEALTH CARE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Family Medicine and Community Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/fmch-2023-002602","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PRIMARY HEALTH CARE","Score":null,"Total":0}
Potential applications and implications of large language models in primary care.
The recent release of highly advanced generative artificial intelligence (AI) chatbots, including ChatGPT and Bard, which are powered by large language models (LLMs), has attracted growing mainstream interest over its diverse applications in clinical practice, including in health and healthcare. The potential applications of LLM-based programmes in the medical field range from assisting medical practitioners in improving their clinical decision-making and streamlining administrative paperwork to empowering patients to take charge of their own health. However, despite the broad range of benefits, the use of such AI tools also comes with several limitations and ethical concerns that warrant further consideration, encompassing issues related to privacy, data bias, and the accuracy and reliability of information generated by AI. The focus of prior research has primarily centred on the broad applications of LLMs in medicine. To the author's knowledge, this is, the first article that consolidates current and pertinent literature on LLMs to examine its potential in primary care. The objectives of this paper are not only to summarise the potential benefits, risks and challenges of using LLMs in primary care, but also to offer insights into considerations that primary care clinicians should take into account when deciding to adopt and integrate such technologies into their clinical practice.
期刊介绍:
Family Medicine and Community Health (FMCH) is a peer-reviewed, open-access journal focusing on the topics of family medicine, general practice and community health. FMCH strives to be a leading international journal that promotes ‘Health Care for All’ through disseminating novel knowledge and best practices in primary care, family medicine, and community health. FMCH publishes original research, review, methodology, commentary, reflection, and case-study from the lens of population health. FMCH’s Asian Focus section features reports of family medicine development in the Asia-pacific region. FMCH aims to be an exemplary forum for the timely communication of medical knowledge and skills with the goal of promoting improved health care through the practice of family and community-based medicine globally. FMCH aims to serve a diverse audience including researchers, educators, policymakers and leaders of family medicine and community health. We also aim to provide content relevant for researchers working on population health, epidemiology, public policy, disease control and management, preventative medicine and disease burden. FMCH does not impose any article processing charges (APC) or submission charges.