人工智能和数据分析显示有两种不同多发性硬化症亚型, 发展模式不同. AI and data analysis reveal two distinct multiple sclerosis subtypes with different progression patterns.

科学家通过人工智能、血液测试和磁共振扫描发现了两种新的生物子型多发性硬化症生物亚型,对600-634名病人的数据进行了分析。 Scientists have discovered two new biological subtypes of multiple sclerosis using AI, blood tests, and MRI scans, analyzing data from 600–634 patients. 早期SNfL子类型显示,神经损伤标记和早期电磁脉冲损害高,表明正在发生攻击性的进展,而迟到的SNfL子类型则表明,在关键区域,生物标志高位延迟,但早期脑量损失减少。 The early-sNfL subtype shows high nerve damage markers and early corpus callosum damage, suggesting aggressive progression, while the late-sNfL subtype features delayed biomarker elevation but early brain volume loss in critical regions. 这一突破由伦敦大学学院和皇后广场分析研究所牵头,揭示出超越基于症状的传统分类的不同疾病轨迹,为针对生物特征的个性化监测和治疗铺平了道路。 This breakthrough, led by University College London and Queen Square Analytics, reveals distinct disease trajectories beyond traditional symptom-based classifications, paving the way for personalized monitoring and treatments tailored to biological profiles.