Literature DB >> 34926780

pySuStaIn: a Python implementation of the Subtype and Stage Inference algorithm.

Leon M Aksman1,2, Peter A Wijeratne2, Neil P Oxtoby2, Arman Eshaghi2,3, Cameron Shand2, Andre Altmann2, Daniel C Alexander2, Alexandra L Young4.   

Abstract

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 modelling situations within a single, consistent architecture.

Entities:  

Keywords:  Disease progression modeling; disease heterogeneity; disease staging; disease subtyping

Year:  2021        PMID: 34926780      PMCID: PMC8682799          DOI: 10.1016/j.softx.2021.100811

Source DB:  PubMed          Journal:  SoftwareX


  16 in total

Review 1.  Clinical, genetic and pathological heterogeneity of frontotemporal dementia: a review.

Authors:  Harro Seelaar; Jonathan D Rohrer; Yolande A L Pijnenburg; Nick C Fox; John C van Swieten
Journal:  J Neurol Neurosurg Psychiatry       Date:  2010-10-22       Impact factor: 10.154

2.  Estimating long-term multivariate progression from short-term data.

Authors:  Michael C Donohue; Hélène Jacqmin-Gadda; Mélanie Le Goff; Ronald G Thomas; Rema Raman; Anthony C Gamst; Laurel A Beckett; Clifford R Jack; Michael W Weiner; Jean-François Dartigues; Paul S Aisen
Journal:  Alzheimers Dement       Date:  2014-03-20       Impact factor: 21.566

3.  Neuropathologically defined subtypes of Alzheimer's disease with distinct clinical characteristics: a retrospective study.

Authors:  Melissa E Murray; Neill R Graff-Radford; Owen A Ross; Ronald C Petersen; Ranjan Duara; Dennis W Dickson
Journal:  Lancet Neurol       Date:  2011-07-27       Impact factor: 44.182

4.  Heterogeneity of multiple sclerosis lesions: implications for the pathogenesis of demyelination.

Authors:  C Lucchinetti; W Brück; J Parisi; B Scheithauer; M Rodriguez; H Lassmann
Journal:  Ann Neurol       Date:  2000-06       Impact factor: 10.422

5.  Ordinal SuStaIn: Subtype and Stage Inference for Clinical Scores, Visual Ratings, and Other Ordinal Data.

Authors:  Alexandra L Young; Jacob W Vogel; Leon M Aksman; Peter A Wijeratne; Arman Eshaghi; Neil P Oxtoby; Steven C R Williams; Daniel C Alexander
Journal:  Front Artif Intell       Date:  2021-08-12

6.  Probabilistic disease progression modeling to characterize diagnostic uncertainty: Application to staging and prediction in Alzheimer's disease.

Authors:  Marco Lorenzi; Maurizio Filippone; Giovanni B Frisoni; Daniel C Alexander; Sebastien Ourselin
Journal:  Neuroimage       Date:  2017-10-24       Impact factor: 6.556

7.  Disease Progression Modeling in Chronic Obstructive Pulmonary Disease.

Authors:  Alexandra L Young; Felix J S Bragman; Bojidar Rangelov; MeiLan K Han; Craig J Galbán; David A Lynch; David J Hawkes; Daniel C Alexander; John R Hurst
Journal:  Am J Respir Crit Care Med       Date:  2020-02-01       Impact factor: 21.405

8.  Associations of Plasma Phospho-Tau217 Levels With Tau Positron Emission Tomography in Early Alzheimer Disease.

Authors:  Shorena Janelidze; David Berron; Ruben Smith; Olof Strandberg; Nicholas K Proctor; Jeffrey L Dage; Erik Stomrud; Sebastian Palmqvist; Niklas Mattsson-Carlgren; Oskar Hansson
Journal:  JAMA Neurol       Date:  2021-02-01       Impact factor: 18.302

9.  Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data.

Authors:  Declan Chard; Olga Ciccarelli; Arman Eshaghi; Alexandra L Young; Peter A Wijeratne; Ferran Prados; Douglas L Arnold; Sridar Narayanan; Charles R G Guttmann; Frederik Barkhof; Daniel C Alexander; Alan J Thompson
Journal:  Nat Commun       Date:  2021-04-06       Impact factor: 14.919

10.  Biological subtypes of Alzheimer disease: A systematic review and meta-analysis.

Authors:  Daniel Ferreira; Agneta Nordberg; Eric Westman
Journal:  Neurology       Date:  2020-02-11       Impact factor: 9.910

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