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Development and Validation of an Automated Image-Based Deep Learning Platform for Sarcopenia Assessm...

Development and Validation of an Automated Image-Based Deep Learning Platform for Sarcopenia Assessm...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10415962

Development and Validation of an Automated Image-Based Deep Learning Platform for Sarcopenia Assessment in Head and Neck Cancer

About this item

Full title

Development and Validation of an Automated Image-Based Deep Learning Platform for Sarcopenia Assessment in Head and Neck Cancer

Publisher

United States: American Medical Association

Journal title

JAMA network open, 2023-08, Vol.6 (8), p.e2328280

Language

English

Formats

Publication information

Publisher

United States: American Medical Association

More information

Scope and Contents

Contents

Sarcopenia is an established prognostic factor in patients with head and neck squamous cell carcinoma (HNSCC); the quantification of sarcopenia assessed by imaging is typically achieved through the skeletal muscle index (SMI), which can be derived from cervical skeletal muscle segmentation and cross-sectional area. However, manual muscle segmentati...

Alternative Titles

Full title

Development and Validation of an Automated Image-Based Deep Learning Platform for Sarcopenia Assessment in Head and Neck Cancer

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10415962

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10415962

Other Identifiers

ISSN

2574-3805

E-ISSN

2574-3805

DOI

10.1001/jamanetworkopen.2023.28280

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