Evaluation of word embedding models to extract and predict surgical data in breast cancer.

Sgroi, Giuseppe; Russo, Giulia; Maglia, Anna; Catanuto, Giuseppe; Barry, Peter; Karakatsanis, Andreas; Rocco, Nicola; Pappalardo, Francesco

Sgroi, Giuseppe; Russo, Giulia; Maglia, Anna; Catanuto, Giuseppe; Barry, Peter; Karakatsanis, Andreas; Rocco, Nicola; Pappalardo, Francesco.

Afiliación

Sgroi G; Department of Mathematics and Computer Science, University of Catania, 95125, Catania, Italy.
Russo G; Department of Drug and Health Sciences, University of Catania, 95125, Catania, Italy.
Maglia A; G.RE.T.A. Group for Reconstructive and Therapeutic Advancements, Catania, Italy.
Catanuto G; G.RE.T.A. Group for Reconstructive and Therapeutic Advancements, Catania, Italy.
Barry P; Multidisciplinary Breast Unit, Azienda Ospedaliera Cannizzaro, Catania, Italy.
Karakatsanis A; G.RE.T.A. Group for Reconstructive and Therapeutic Advancements, Catania, Italy.
Rocco N; G.RE.T.A. Group for Reconstructive and Therapeutic Advancements, Catania, Italy.

BMC Bioinformatics ; 22(Suppl 14): 631, 2022 Nov 16.

Article en En | MEDLINE | ID: mdl-36384559

Asunto(s)

Inteligencia Artificial; Neoplasias de la Mama; Humanos; Femenino; Neoplasias de la Mama/cirugía; Procesamiento de Lenguaje Natural; Aprendizaje Automático

Palabras clave

Breast cancer; Machine learning; Natural language processing; Word embeddings; Word2Vec

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Inteligencia Artificial Tipo de estudio: Prognostic_studies / Qualitative_research / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Italia

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