Evaluation of a prediction model for colorectal cancer: retrospective analysis of 2.5 million patient records.

Birks, Jacqueline; Bankhead, Clare; Holt, Tim A; Fuller, Alice; Patnick, Julietta

Birks, Jacqueline; Bankhead, Clare; Holt, Tim A; Fuller, Alice; Patnick, Julietta.

Afiliação

Birks J; Oxford Biomedical Research Centre, Oxford University, Botnar Research Institute, Windmill Rd, Oxford, OX7 3LD, United Kingdom.
Bankhead C; Nuffield Department of Primary Care Health Sciences, Oxford University, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom.
Holt TA; Nuffield Department of Primary Care Health Sciences, Oxford University, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom.
Fuller A; Nuffield Department of Primary Care Health Sciences, Oxford University, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom.
Patnick J; Cancer Epidemiology Unit, Nuffield Department of Population Health, Oxford University, Richard Doll Building, Old Road Campus, Oxford, OX3 7LF, United Kingdom.

Cancer Med ; 6(10): 2453-2460, 2017 Oct.

Article em En | MEDLINE | ID: mdl-28941187

Assuntos

Neoplasias Colorretais/diagnóstico; Neoplasias Colorretais/epidemiologia; Modelos Teóricos; Adulto; Idoso; Idoso de 80 Anos ou mais; Algoritmos; Estudos de Casos e Controles; Registros Eletrônicos de Saúde; Feminino; Humanos; Aprendizado de Máquina; Masculino; Pessoa de Meia-Idade; Vigilância da População; Prognóstico; Curva ROC; Estudos Retrospectivos; Medição de Risco

Palavras-chave

Blood cell count; colorectal neoplasms; early detection of cancer; electronic health records; machine learning; risk assessment

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Modelos Teóricos Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2017 Tipo de documento: Article

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