Application of Artificial Neural Network Models to Differentiate Between Complicated and Uncomplicated Acute Appendicitis.

Lin, Hui-An; Lin, Li-Tsung; Lin, Sheng-Feng

Lin, Hui-An; Lin, Li-Tsung; Lin, Sheng-Feng.

Afiliação

Lin HA; Department of Emergency Medicine, Taipei Medical University Hospital, 250 Wu-Hsing Street, Taipei, Taiwan.
Lin LT; Department of Emergency Medicine, School of Medicine, College of Medicine , Taipei Medical University, Taipei, Taiwan.
Lin SF; Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.

J Med Syst ; 47(1): 38, 2023 Mar 23.

Article em En | MEDLINE | ID: mdl-36952043

Assuntos

Apendicite; Apêndice; Humanos; Apendicite/diagnóstico; Apendicite/cirurgia; Doença Aguda; Sensibilidade e Especificidade; Estudos Retrospectivos

Palavras-chave

Acute appendicitis; Artificial neural network; Complicated appendicitis; Emergency department; Receiver of operating characteristic curve

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Apendicite / Apêndice Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Med Syst Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Taiwan

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