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A deep learning framework identifies dimensional representations of Alzheimer’s Disease from brain s...

A deep learning framework identifies dimensional representations of Alzheimer’s Disease from brain s...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_bc622eef4986462d950294c8155877a6

A deep learning framework identifies dimensional representations of Alzheimer’s Disease from brain structure

About this item

Full title

A deep learning framework identifies dimensional representations of Alzheimer’s Disease from brain structure

Publisher

London: Nature Publishing Group UK

Journal title

Nature communications, 2021-12, Vol.12 (1), p.7065-7065, Article 7065

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Heterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We describe and validate Smile-GAN (SeMI-supervised cLustEring-Generative Adversarial Network), a semi-supervised deep-clustering method, which examines neuroanatomical heterogeneity contrasted against normal brain structure, to identify disease subtypes through neuro...

Alternative Titles

Full title

A deep learning framework identifies dimensional representations of Alzheimer’s Disease from brain structure

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_bc622eef4986462d950294c8155877a6

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_bc622eef4986462d950294c8155877a6

Other Identifiers

ISSN

2041-1723

E-ISSN

2041-1723

DOI

10.1038/s41467-021-26703-z

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