人工智能驱动的个性化护理对多发性硬化症患者的未来
Jelle Praet1, Lina Anderhalten2, Giancarlo Comi3,4
1icometrix NV, Leuven, Belgium.
Frontiers in immunology
|September 3, 2024
概括
优化多发性硬化症 (MS) 的治疗是复杂的,因为疾病的异质性. 使用人工智能的主动,数据驱动的方法可以个性化护理,并改善MS患者的治疗结果.
科学领域:
- 神经免疫学 神经免疫学
- 神经学 神经学
- 个性化医疗是个性化的医疗.
背景情况:
- 多发性硬化症 (MS) 是一种免疫媒介的中枢神经系统疾病,导致逐渐残疾.
- 目前的多发性硬化症治疗旨在减少复发和减缓进展,以改善生活质量.
- 由于MS进展的显著临床和亚临床异质性,治疗优化具有挑战性.
研究的目的:
- 讨论优化MS (pwMS) 患者治疗的挑战.
- 探索转向积极主动,数据驱动,个性化医疗的MS护理.
- 介绍CLAIMS项目作为人工智能辅助个性化MS治疗的一个例子.
主要方法:
- 讨论MS治疗优化方面的挑战.
- 对多发性硬化症个性化医疗方法的描述.
- 介绍CLAIMS平台的整体患者数据集成.
- 利用人工智能用于MS的预后建模.
主要成果:
- 克莱姆斯项目展示了一个整体患者数据和生物标志物集成的平台.
- 人工智能支持的预后建模可以实现个性化的治疗策略.
- 以数据为导向的方法可以解决多发性硬化症的异质性.
结论:
- 由人工智能和综合数据支持的个性化医疗,有望优化多发性硬化护理.
- 积极的,数据驱动的策略对于管理多发性硬化症异质性至关重要.
- 克莱姆斯 (CLAIMS) 项目是改善多发性硬化症患者治疗结果的未来方向的一个例子.
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