一个可以植入的设备与患者交谈,并学会共同管理
medRxiv : the preprint server for health sciences
|February 6, 2026
概括
一个新的设备平台使用人工智能 (AI) 和大型语言模型与患者交谈,改善管理和设备个性化. 这种由人工智能驱动的系统增强了患者和医疗设备之间的通信,以获得更好的健康结果.
科学领域:
- 神经科学和生物医学工程
- 医疗保健中的人工智能
- 医疗器械技术 医疗器械技术
背景情况:
- 影响全球7000万,其中三分之一的人经历了抗药性发作.
- 目前的植入式设备提供了控制,但缺乏实时患者通信.
- 这种沟通差距限制了个性化学习和患者-提供者反循环.
研究的目的:
- 介绍一种新的设备平台,使患者和人工智能之间能够进行双向对话,以共同管理.
- 开发一种可以从患者数据和互动中学习以个性化护理的AI代理.
- 为了证明平台在患者中的有效性和可用性.
主要方法:
- 住院原型将头皮和内脑电图 (EEG) 连接起来,以保护大型语言模型.
- 人工智能代理从大脑活动中摄取生物标志物 (意识,睡眠,认知,风险).
- 智能手机应用程序促进双向通信,症状记录和AI自我再培训.
主要成果:
- 该平台在住院监测期间在13名患者中展示了有效的联合管理.
- 抓获检测算法在几天内自动优化了精度,减少了手动编程时间.
- 患者对人工智能驱动的洞察报告了积极的反应,并将系统评为高度可用.
结论:
- 开发的平台为医疗设备提供了一个可扩展,可适应的解决方案,以共同管理.
- 这种人工智能驱动的对话方法提高了患者的参与度,并个性化了治疗.
- 该系统具有广泛应用的潜力,可用于管理各种疾病.
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