Multiple Sclerosis disease states as identified by unsupervised machine learning on multimodal longitudinal patient trajectories

被引：0

作者：

Ganjgahi, H. ^{[1
]}

Haring, D. A. ^{[2
]}

Graham, G. ^{[2
]}

Sun, Y. ^{[3
]}

Gardiner, S. ^{[3
]}

Su, W. ^{[4
]}

Kieseier, B. C. ^{[2
]}

Nichols, T. E. ^{[3
]}

Arnold, D. L. ^{[5
]}

Bermel, R. A. ^{[6
]}

Wiendl, H. ^{[7
]}

Holmes, C. C. ^{[8
]}

机构：

[1] Univ Oxford, Dept Stat, Oxford, England

[2] Novartis Pharma AG, Basel, Switzerland

[3] Univ Oxford, Oxford Big Data Inst, Nuffield Dept Hlth, Li Ka Shing Ctr Hlth Informat & Discovery, Oxford, England

[4] Novartis Pharmaceut, E Hanover, NJ USA

[5] McGill Univ, Montreal Neurol Inst & Hosp, Brain Imaging Ctr, Montreal, PQ, Canada

[6] Cleveland Clin, Dept Neurol, Mellen MS Ctr, Cleveland, OH 44106 USA

[7] Univ Hosp Munster, Dept Neurol, Munster, Germany

[8] Univ Oxford, Dept Stat, Oxford, England

来源：

MULTIPLE SCLEROSIS JOURNAL | 2022年 / 28卷 / 3_SUPPL期

关键词：

D O I：

暂无

中图分类号：

R74 [神经病学与精神病学];

学科分类号：

摘要：

P1208

引用

页码：979 / 980

页数：2

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