pySuStaIn: A Python']Python implementation of the Subtype and Stage Inference algorithm

被引:20
|
作者
Aksman, Leon M. [1 ,2 ]
Wijeratne, Peter A. [2 ]
Oxtoby, Neil P. [2 ]
Eshaghi, Arman [2 ,3 ]
Shand, Cameron [2 ]
Altmann, Andre [2 ]
Alexander, Daniel C. [2 ]
Young, Alexandra L. [4 ]
机构
[1] Univ Southern Calif, Keck Sch Med, Stevens Neuroimaging & Informat Inst, Los Angeles, CA 90007 USA
[2] UCL, Dept Comp Sci & Med Phys, Ctr Med Image Comp, London, England
[3] UCL, Fac Brain Sci, UCL Queen Sq Inst Neurol, Dept Neuroinflammat,Queen Sq Multiple Sclerosis C, London, England
[4] Kings Coll London, Inst Psychiat Psychol & Neurosci, Dept Neuroimaging, London, England
基金
美国国家卫生研究院; 英国医学研究理事会;
关键词
Disease progression modeling; Disease heterogeneity; Disease subtyping; Disease staging; ALZHEIMERS-DISEASE; HETEROGENEITY; PROGRESSION; MODEL;
D O I
10.1016/j.softx.2021.100811
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Progressive disorders are highly heterogeneous. Symptom-based clinical classification of these disorders may not reflect the underlying pathobiology. Data-driven subtyping and staging of patients has the potential to disentangle the complex spatiotemporal patterns of disease progression. Tools that enable this are in high demand from clinical and treatment-development communities. Here we describe the pySuStaIn software package, a Python-based implementation of the Subtype and Stage Inference (SuStaIn) algorithm. SuStaIn unravels the complexity of heterogeneous diseases by inferring multiple disease progression patterns (subtypes) and individual severity (stages) from cross-sectional data. The primary aims of pySuStaIn are to enable widespread application and translation of SuStaIn via an accessible Python package that supports simple extension and generalization to novel modeling situations within a single, consistent architecture. (C) 2021 The Authors. Published by Elsevier B.V.
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页数:8
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