Artificial intelligence in breast cancer imaging: risk stratification, lesion detection and classification, treatment planning and prognosis-a narrative review.

Cè, Maurizio; Caloro, Elena; Pellegrino, Maria E; Basile, Mariachiara; Sorce, Adriana; Fazzini, Deborah; Oliva, Giancarlo; Cellina, Michaela

Cè, Maurizio; Caloro, Elena; Pellegrino, Maria E; Basile, Mariachiara; Sorce, Adriana; Fazzini, Deborah; Oliva, Giancarlo; Cellina, Michaela.

Affiliation

Cè M; Postgraduate School in Diagnostic and Interventional Radiology, University of Milan, 20122 Milan, Italy.
Caloro E; Postgraduate School in Diagnostic and Interventional Radiology, University of Milan, 20122 Milan, Italy.
Pellegrino ME; Postgraduate School in Diagnostic and Interventional Radiology, University of Milan, 20122 Milan, Italy.
Basile M; Postgraduate School in Diagnostic and Interventional Radiology, University of Milan, 20122 Milan, Italy.
Sorce A; Postgraduate School in Diagnostic and Interventional Radiology, University of Milan, 20122 Milan, Italy.
Fazzini D; Centro Diagnostico Italiano, 20147 Milan, Italy.
Oliva G; Department of Radiology, ASST Fatebenefratelli Sacco, 20121 Milan, Italy.
Cellina M; Department of Radiology, ASST Fatebenefratelli Sacco, 20121 Milan, Italy.

Explor Target Antitumor Ther ; 3(6): 795-816, 2022.

Article in En | MEDLINE | ID: mdl-36654817

Key words

Breast cancer imaging; artificial intelligence; computer-aided detection; digital breast tomosynthesis; machine learning; magnetic resonance imaging; mammogram

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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Diagnostic_studies / Etiology_studies / Guideline / Prognostic_studies / Risk_factors_studies Language: En Journal: Explor Target Antitumor Ther Year: 2022 Document type: Article Affiliation country: Italy Country of publication: United States

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