Study workflow.

<p>Outpatient visits at the Memory Diagnostic Center with a Clinical Dementia Rating recorded in the Washington University School of Medicine Electronic Health Records were included. Feature selection was performed to identify the optimal set of features for clustering. The SillyPutty algorith...

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Main Author: Sayantan Kumar (20208872) (author)
Other Authors: Inez Y. Oh (20208875) (author), Suzanne E. Schindler (7057418) (author), Nupur Ghoshal (12019647) (author), Zachary Abrams (3509720) (author), Philip R. O. Payne (9958153) (author)
Published: 2024
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author Sayantan Kumar (20208872)
author2 Inez Y. Oh (20208875)
Suzanne E. Schindler (7057418)
Nupur Ghoshal (12019647)
Zachary Abrams (3509720)
Philip R. O. Payne (9958153)
author2_role author
author
author
author
author
author_facet Sayantan Kumar (20208872)
Inez Y. Oh (20208875)
Suzanne E. Schindler (7057418)
Nupur Ghoshal (12019647)
Zachary Abrams (3509720)
Philip R. O. Payne (9958153)
author_role author
dc.creator.none.fl_str_mv Sayantan Kumar (20208872)
Inez Y. Oh (20208875)
Suzanne E. Schindler (7057418)
Nupur Ghoshal (12019647)
Zachary Abrams (3509720)
Philip R. O. Payne (9958153)
dc.date.none.fl_str_mv 2024-11-14T18:30:19Z
dc.identifier.none.fl_str_mv 10.1371/journal.pone.0313425.g001
dc.relation.none.fl_str_mv https://figshare.com/articles/figure/Study_workflow_/27735116
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Medicine
Neuroscience
Biotechnology
Mental Health
Virology
revealing new insights
ongoing temporal relationship
expensive imaging biomarkers
xlink "> dementia
dementia specialty clinics
dementia &# 8217
cognitive assessment scores
estimate subtypes within
driven unsupervised clustering
dementia using data
related dementia
dementia subtyping
driven subtypes
cognitive profiles
mild dementia
underlying heterogeneity
significant enough
results showed
recent research
patients seen
impair function
hierarchical clustering
finding data
examining heterogeneity
disease progression
different symptoms
different rates
daily living
current studies
clustering analysis
baseline visits
allowing us
dc.title.none.fl_str_mv Study workflow.
dc.type.none.fl_str_mv Image
Figure
info:eu-repo/semantics/publishedVersion
image
description <p>Outpatient visits at the Memory Diagnostic Center with a Clinical Dementia Rating recorded in the Washington University School of Medicine Electronic Health Records were included. Feature selection was performed to identify the optimal set of features for clustering. The SillyPutty algorithm [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0313425#pone.0313425.ref027" target="_blank">27</a>] with hierarchical clustering was used to identify clusters from longitudinal patient visits. Identified clusters were analyzed for variability (heterogeneity) in cognitive characteristics. Patient transitions between subtypes across multiple visits were examined for variability in rate of disease progression.</p>
eu_rights_str_mv openAccess
id Manara_58fa9cdcbb25c01101cccded54aea18e
identifier_str_mv 10.1371/journal.pone.0313425.g001
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/27735116
publishDate 2024
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling Study workflow.Sayantan Kumar (20208872)Inez Y. Oh (20208875)Suzanne E. Schindler (7057418)Nupur Ghoshal (12019647)Zachary Abrams (3509720)Philip R. O. Payne (9958153)MedicineNeuroscienceBiotechnologyMental HealthVirologyrevealing new insightsongoing temporal relationshipexpensive imaging biomarkersxlink "> dementiadementia specialty clinicsdementia &# 8217cognitive assessment scoresestimate subtypes withindriven unsupervised clusteringdementia using datarelated dementiadementia subtypingdriven subtypescognitive profilesmild dementiaunderlying heterogeneitysignificant enoughresults showedrecent researchpatients seenimpair functionhierarchical clusteringfinding dataexamining heterogeneitydisease progressiondifferent symptomsdifferent ratesdaily livingcurrent studiesclustering analysisbaseline visitsallowing us<p>Outpatient visits at the Memory Diagnostic Center with a Clinical Dementia Rating recorded in the Washington University School of Medicine Electronic Health Records were included. Feature selection was performed to identify the optimal set of features for clustering. The SillyPutty algorithm [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0313425#pone.0313425.ref027" target="_blank">27</a>] with hierarchical clustering was used to identify clusters from longitudinal patient visits. Identified clusters were analyzed for variability (heterogeneity) in cognitive characteristics. Patient transitions between subtypes across multiple visits were examined for variability in rate of disease progression.</p>2024-11-14T18:30:19ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0313425.g001https://figshare.com/articles/figure/Study_workflow_/27735116CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/277351162024-11-14T18:30:19Z
spellingShingle Study workflow.
Sayantan Kumar (20208872)
Medicine
Neuroscience
Biotechnology
Mental Health
Virology
revealing new insights
ongoing temporal relationship
expensive imaging biomarkers
xlink "> dementia
dementia specialty clinics
dementia &# 8217
cognitive assessment scores
estimate subtypes within
driven unsupervised clustering
dementia using data
related dementia
dementia subtyping
driven subtypes
cognitive profiles
mild dementia
underlying heterogeneity
significant enough
results showed
recent research
patients seen
impair function
hierarchical clustering
finding data
examining heterogeneity
disease progression
different symptoms
different rates
daily living
current studies
clustering analysis
baseline visits
allowing us
status_str publishedVersion
title Study workflow.
title_full Study workflow.
title_fullStr Study workflow.
title_full_unstemmed Study workflow.
title_short Study workflow.
title_sort Study workflow.
topic Medicine
Neuroscience
Biotechnology
Mental Health
Virology
revealing new insights
ongoing temporal relationship
expensive imaging biomarkers
xlink "> dementia
dementia specialty clinics
dementia &# 8217
cognitive assessment scores
estimate subtypes within
driven unsupervised clustering
dementia using data
related dementia
dementia subtyping
driven subtypes
cognitive profiles
mild dementia
underlying heterogeneity
significant enough
results showed
recent research
patients seen
impair function
hierarchical clustering
finding data
examining heterogeneity
disease progression
different symptoms
different rates
daily living
current studies
clustering analysis
baseline visits
allowing us