在神经退行性疾病中,人工智能驱动的神经调节:在混乱中精确,在损失中学习
Andrea Calderone1, Desirèe Latella1, Elvira La Fauci2
1IRCCS Centro Neurolesi Bonino-Pulejo, S.S. 113 Via Palermo, C.da Casazza, 98124 Messina, Italy.
Biomedicines
|September 27, 2025
概括
人工智能 (AI) 增强了神经退行性疾病 (如阿尔茨海默氏症和帕金森症) 的神经调节. 人工智能可以实现个性化,适应性疗法,超越固定的协议,改善患者的治疗结果.
科学领域:
- 神经科学是一个神经科学.
- 生物医学工程 生物医学工程
- 人工智能的人工智能
背景情况:
- 神经退行性疾病 (例如,阿尔茨海默氏症,帕金森症,多发性硬化症) 导致逐渐的网络功能障碍,挑战传统的神经康复.
- 神经调节技术 (DBS,TMS,tDCS,VNS) 和人工智能 (AI) 已经进步,提供了新的治疗途径.
研究的目的:
- 审查人工智能和神经调节在神经康复中的交集.
- 探索数据驱动的人工智能模型如何个性化神经调节疗法,并增强神经退行性疾病的功能结果.
主要方法:
- 一个叙事评论,综合了PubMed,Embase,Scopus和参考链的同行评审研究.
- 专注于自适应/闭环系统,预测建模和生物标记指导协议在AI增强的神经调节.
主要成果:
- 人工智能优化了神经调节器件的编程,并使状态依赖的适应性刺激成为可能.
- 人工智能支持使用多模式生物标志物 (神经,运动,行为) 的临床决策.
- 关键的挑战包括数据质量,模型可解释性,安全性和道德/监管监督.
结论:
- 人工智能驱动的神经调节将神经康复转变为适应性,针对患者的特定护理.
- 未来的进展需要外部验证,标准化报告,临床医生监督和保护隐私的分析.
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