基于ChatGPT的人工智能技术在全科医疗服务中的应用研究

田甜; 张飞; 张璇; 王佳贺

doi:10.16766/j.cnki.issn.1674-4152.003988

基于ChatGPT的人工智能技术在全科医疗服务中的应用研究

doi: 10.16766/j.cnki.issn.1674-4152.003988

中国医科大学附属盛京医院全科医学科，辽宁沈阳 110000

基金项目:

中国医科大学第二临床学院“十四五”第一批医学教育科学研究课题 SJKF-2022ZD04

详细信息

通讯作者:
王佳贺，E-mail：wangjhcmusj@163.com

中图分类号: R499 R192.3
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- 文章访问数: 19
- HTML全文浏览量: 10
- PDF下载量: 3
- 被引次数: 0
出版历程
- 收稿日期: 2024-05-28
- 网络出版日期: 2025-08-14

Research on the application of artificial intelligence technology based on ChatGPT in general medical services

Department of General Practice, Sheng Jing Hospital of China Medical University, Shenyang, Liaoning 110000, China

摘要

摘要: 随着信息技术的快速发展，人工智能(AI)在医疗健康领域的应用已成为研究热点。以ChatGPT为代表的对话生成模型，通过高效信息处理与自然语言交互能力，为提升医疗服务的效率与质量提供了创新性解决方案。本研究旨在系统分析ChatGPT在全科医疗中的应用潜力，探讨其与全科医生工作流程的整合策略及实施挑战，并评估其对医疗服务质量的优化效果。研究结果表明，ChatGPT在医学知识更新、临床决策支持及患者健康管理中具有显著优势。通过开发个性化医疗信息推送系统和智能化患者信息处理平台，可有效缓解全科医生的工作负荷。ChatGPT的上下文学习(ICL)能力可精准匹配医生需求；病历自动摘要功能则显著提升诊疗效率；针对远程医疗需求增长，可构建基于ChatGPT的智能健康管理平台。整合过程中需遵循人机协同、数据安全与系统可持续性原则，明确AI的辅助定位。未来研究应聚焦算法优化、隐私保护机制及跨学科协作模式，以推动AI技术在全科医疗中的深度整合与精准应用。
- 全科医生 /
- ChatGPT /
- 人工智能 /
- 自然语言处理 /
- 医工结合
Abstract: In the contemporary era, characterized by accelerated advancements in information technology, the field of artificial intelligence (AI) in healthcare has emerged as a prominent area of research focus. Conversational generative models, such as ChatGPT, offer innovative solutions to improve the efficiency and quality of medical services through their powerful information processing and natural language interaction capabilities. This study systematically investigates the potential of ChatGPT in general practice, exploring strategies and challenges for integrating it into the workflow of general practitioners, and evaluating its impact on optimizing healthcare service quality. The findings indicate that ChatGPT has advantages in medical knowledge updating, clinical decision support and patient health management. Specifically, the development of personalized medical information delivery systems and intelligent patient data processing platforms has the potential to alleviate the workload of general practitioners. The In-Context Learning (ICL) capability of ChatGPT has been demonstrated to align with physicians' needs with a high degree of precision, while its automated medical record summarization function has been shown to substantially improve diagnostic efficiency. In order to achieve effective integrations, it must adhere to principles of human. The emphasis is on the auxiliary role of AI, with particular reference to collaboration, date security and system sustainability. It is recommended that future research place a priority on the optimization of algorithms, the development of privacy protection mechanisms, and the establishment of interdisciplinary collaboration models. These measures are considered essential for the advancement of deep integration and precise application of AI technologies in general practice.
- General practitioners /
- ChatGPT /
- Artificial intelligence /
- Natural language processing /
- Medical-engineering integration

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