An artificial neural network for the prediction of the risk of malignancy in category III Bethesda thyroid lesions.

Saini, Tarunpreet; Saikia, Uma Nahar; Dey, Pranab

Saini, Tarunpreet; Saikia, Uma Nahar; Dey, Pranab.

Afiliación

Saini T; Department of Pathology, Postgraduate Institute of Medical Education and Research, Chandigarh, India.
Saikia UN; Department of Histopathology, Post Graduate Institute of Medical Education and Research, Chandigarh, India.
Dey P; Department of Cytology, Post Graduate Institute of Medical Education and Research, Chandigarh, India.

Cytopathology ; 34(1): 48-54, 2023 Jan.

Article en En | MEDLINE | ID: mdl-36136062

Asunto(s)

Adenocarcinoma Folicular; Neoplasias de la Tiroides; Nódulo Tiroideo; Humanos; Adenocarcinoma Folicular/patología; Nódulo Tiroideo/diagnóstico; Nódulo Tiroideo/patología; Neoplasias de la Tiroides/diagnóstico; Neoplasias de la Tiroides/patología; Redes Neurales de la Computación; Estudios Retrospectivos

Palabras clave

artificial intelligence; artificial neural network; atypia of undetermined significance; follicular lesion of undetermined significance; thyroid

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Tiroides / Nódulo Tiroideo / Adenocarcinoma Folicular Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Cytopathology Asunto de la revista: PATOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: India

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