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18 F‑FDG PET/CT based radiomics features improve prediction of prognosis: multiple machine learning...

18 F‑FDG PET/CT based radiomics features improve prediction of prognosis: multiple machine learning...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmed_primary_37370013

18 F‑FDG PET/CT based radiomics features improve prediction of prognosis: multiple machine learning algorithms and multimodality applications for multiple myeloma

About this item

Full title

18 F‑FDG PET/CT based radiomics features improve prediction of prognosis: multiple machine learning algorithms and multimodality applications for multiple myeloma

Publisher

England

Journal title

BMC medical imaging, 2023-06, Vol.23 (1), p.87

Language

English

Formats

Publication information

Publisher

England

More information

Scope and Contents

Contents

Multiple myeloma (MM), the second most hematological malignancy, have been studied extensively in the prognosis of the clinical parameters, however there are only a few studies have discussed the role of dual modalities and multiple algorithms of
F-FDG (
F-fluorodeoxyglucose) PET/CT based radiomics signatures for prognosis in MM patients. We...

Alternative Titles

Full title

18 F‑FDG PET/CT based radiomics features improve prediction of prognosis: multiple machine learning algorithms and multimodality applications for multiple myeloma

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_pubmed_primary_37370013

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmed_primary_37370013

Other Identifiers

E-ISSN

1471-2342

DOI

10.1186/s12880-023-01033-2

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