Cancer Diagnosis Using Deep Learning: A Bibliographic Review.

Munir, Khushboo; Elahi, Hassan; Ayub, Afsheen; Frezza, Fabrizio; Rizzi, Antonello

Munir, Khushboo; Elahi, Hassan; Ayub, Afsheen; Frezza, Fabrizio; Rizzi, Antonello.

Afiliação

Munir K; Department of Information Engineering, Electronics and Telecommunications (DIET), Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy. khushboo.munir@uniroma1.it.
Elahi H; Department of Mechanical and Aerospace Engineering (DIMA), Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy.
Ayub A; Department of Basic and Applied Science for Engineering (SBAI), Sapienza University of Rome, Via Antonio Scarpa 14/16, 00161 Rome, Italy.
Frezza F; Department of Information Engineering, Electronics and Telecommunications (DIET), Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy.
Rizzi A; Department of Information Engineering, Electronics and Telecommunications (DIET), Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy.

Cancers (Basel) ; 11(9)2019 Aug 23.

Article em En | MEDLINE | ID: mdl-31450799

Palavras-chave

convolutional neural networks (CNNs); deep autoencoders (DANs); deep learning; generative adversarial models (GANs); long short-term memory (LTSM); recurrent neural networks (RNNs); restricted Boltzmann's machine (RBM)

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Itália

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