数字双胞胎认知:人工智能与生物标志物在生物仿真神经心理学中的整合
Evgenia Gkintoni1,2, Constantinos Halkiopoulos3
1Department of Medicine, University of Patras, 26504 Patras, Greece.
Biomimetics (Basel, Switzerland)
|October 28, 2025
概括
数字双胞胎认知,整合人工智能和多模式生物标志物,使个性化神经心理评估和干预成为可能. 需要进一步的研究来验证这些先进的数字工具的广泛临床使用.
科学领域:
- 神经科学是一个神经科学.
- 人工智能的人工智能
- 数字健康数字健康
背景情况:
- 数字双胞胎认知融合了人工智能和多模式生物标志物,以实现个性化的认知健康.
- 这种方法可以创建用于监测和干预的动态虚拟模型.
- 它代表了神经心理评估的范式转变.
研究的目的:
- 系统地审查人工智能生物标志物在神经心理学框架中的整合.
- 评估这些综合方法的有效性和有效性.
- 确定个性化认知健康的挑战和未来方向.
主要方法:
- 在医学,神经科学和计算机科学数据库中进行系统的文献搜索 (2014-2024年).
- 在研究选择和数据综合方面遵循PRISMA 2020指南.
- 在框架整合,预测准确性和临床翻译方面综合了证据.
主要成果:
- 多模式数据集成显著优于单模式评估.
- 深度学习优于模式识别;传统的ML提供可解释性.
- 框架对神经退行性疾病和MS的早期检测和个性化治疗充满希望.
- 高精度要求往往缺乏外部验证;现实世界的性能较低.
结论:
- 数字双胞胎认知为个性化神经心理学提供了一个新的前沿.
- 有机会进行早期检测,监测和适应性干预.
- 标准化,验证和伦理框架的进步对于临床部署至关重要.
关键词:
人工智能的人工智能是人工智能.生物模拟神经心理学数字生物标志物数字生物标志物数字双胞胎认知数字双胞胎认知多式联运集成多式联运集成神经退行性疾病的神经退行性疾病神经心理学神经心理学个性化认知评估个性化认知评估更多相关视频
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