The Use of Artificial Neural Network to Predict Surgical Outcomes After Inguinal Hernia Repair.
J Surg Res
; 259: 372-378, 2021 03.
Article
em En
| MEDLINE
| ID: mdl-33097206
ABSTRACT
BACKGROUND:
Inguinal hernia repair is one of the most commonly performed surgical procedures. We developed and validated an artificial neural network (ANN) model for the prediction of surgical outcomes and the analysis of risk factors for inguinal hernia repair. MATERIALS ANDMETHODS:
The American College of Surgeons National Surgical Quality Improvement Program was used to find patients who underwent inguinal hernia repair. Using logistic regression and ANN models, we evaluated morbidity, readmission, and mortality using the area under the receiver operating characteristic curves, true-positive rate, true-negative rate, false-positive rate, and false-negative rates.RESULTS:
There was no significant difference in the power of the ANN and logistic regression for predicting mortality, readmission, and all morbidities after inguinal hernia repair. Risk factors for morbidity, readmission, and mortality outcomes identified using ANN were consistent with logistic regression analysis.CONCLUSIONS:
ANNs perform comparably to logistic regression models in the prediction of outcomes after inguinal hernia repair. ANNs may be a useful tool in risk factor analysis of hernia surgery and clinical applications.Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Complicações Pós-Operatórias
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Redes Neurais de Computação
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Procedimentos Cirúrgicos Eletivos
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Herniorrafia
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Hérnia Inguinal
Tipo de estudo:
Etiology_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Adolescent
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Adult
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Aged
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Aged80
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2021
Tipo de documento:
Article