Mortality Prediction in Patients With Breast Cancer by Artificial Neural Network Model and Elastic Net Regression.

Journal: Journal of research in health sciences

PMID: 39996347

Abstract

BACKGROUND: Breast cancer (BC) is the most common cancer in women, and it is important to identify models that can accurately predict mortality in patients with this cancer. The aim of the present study was to use the elastic net regression and artificial neural network (ANN) models in diagnosing and predicting factors affecting BC mortality. A cross-sectional study.

Authors

Anis Esmaeili

Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran.
Ali Karamoozian

Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran.
Abbas Bahrampour

Department of Biostatistics and Epidemiology, Modeling in Health Research Center, Faculty of Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran. abahrampour@yahoo.com.

Keywords

Adult Aged Area Under Curve Breast Neoplasms Cross-Sectional Studies Female Humans Iran Middle Aged Neural Networks, Computer ROC Curve Sensitivity and Specificity

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View on PubMed Access via DOI PubMed (39996347)

Mortality Prediction in Patients With Breast Cancer by Artificial Neural Network Model and Elastic Net Regression.

Abstract

Authors

Keywords

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