为医疗咨询开发基于人工智能的对话式Web应用程序:研究原型研究
1IdeaCoding Lab, Rua Timbopeba, 24, Ouro Preto, 35411000, Brazil, 55 31988624279.
JMIRx med
|October 15, 2025
概括
这项研究将大型语言模型与专门的AI诊断工具集成在一起,创建了一个能够分析医疗图像和预测疾病的智能聊天机器人. 模块化设计允许轻松扩展,增强生物信息学用户体验.
科学领域:
- 人工智能的人工智能
- 医学诊断 医学诊断 医学诊断
- 生物信息学是一种生物信息学.
背景情况:
- 交谈式人工智能,特别是生成性人工智能,是领先的趋势,经常被部署为聊天机器人.
- 开放AI的进步允许整合外部模型,用于专门的聊天机器人功能,超出一般的语言处理.
研究的目的:
- 开发一个智能聊天机器人,将OpenAI的大型语言模型与专门的医疗诊断模型集成在一起.
- 证明将LLMs与外部模型结合起来,用于多式联络,以任务为导向的对话代理.
主要方法:
- 使用转移学习 (谷歌的可教机器) 开发了基于图像的分类器.
- 胸部X射线肺炎检测和光学连贯性断层扫描 (OCT) 分析的综合模型.
- 结合了使用生理数据的TensorFlow.js糖尿病预测模型.
- 设计了一个模块化架构,以便轻松添加新的诊断模型.
主要成果:
- 成功地将聊天机器人与诊断模型集成,显示出与预期行为的轻微偏差.
- 实现了一个功能,根据病情严重程度安排医疗预约.
- 已与OCT和X射线模型进行测试,用于预约安排.
结论:
- 使用人工智能作为服务开发先进的人工智能系统 (图像诊断,聊天机器人集成) 的可行性.
- 强调了人工智能的潜力,以改善生物信息学中的用户体验和可访问性.
- 强调聊天机器人的模块化,以便在未来整合额外的诊断模型.
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