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Artificial intelligence in breast cancer diagnostics.
La Porta, Caterina Am; Zapperi, Stefano.
Affiliation
  • La Porta CA; Department of Environmental Science and Policy, Center for Complexity & Biosystems, University of Milan, via Celoria 10, 20133 Milan, Italy; CNR - Consiglio Nazionale delle Ricerche, Istituto di Biofisica, via Celoria 10, 20133 Milan, Italy. Electronic address: caterina.laporta@unimi.it.
  • Zapperi S; Department of Physics, Center for Complexity & Biosystems, University of Milan, via Celoria 16, 20133 Milan, Italy; CNR - Consiglio Nazionale delle Ricerche, Istituto di Chimica della Materia Condensata e di Tecnologie per l'Energia, Via R. Cozzi 53, 20125 Milano, Italy.
Cell Rep Med ; 3(12): 100851, 2022 12 20.
Article in En | MEDLINE | ID: mdl-36543102
ABSTRACT
Since breast cancer deaths are mainly due to metastasis, predicting the risk that a primary tumor will develop metastasis after a first diagnosis is a central issue that could be addressed by artificial intelligence. To overcome the problem posed by limited availability of standardized datasets, algorithms should include biological insight.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms / Artificial Intelligence Type of study: Diagnostic_studies / Prognostic_studies Limits: Female / Humans Language: En Journal: Cell Rep Med Year: 2022 Document type: Article
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms / Artificial Intelligence Type of study: Diagnostic_studies / Prognostic_studies Limits: Female / Humans Language: En Journal: Cell Rep Med Year: 2022 Document type: Article