Neural networks versus Logistic regression for 30 days all-cause readmission prediction
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چکیده
منابع مشابه
Artificial neural networks versus bivariate logistic regression in prediction diagnosis of patients with hypertension and diabetes
Background: Diabetes and hypertension are important non-communicable diseases and their prevalence is important for health authorities. The aim of this study was to determine the predictive precision of the bivariate Logistic Regression (LR) and Artificial Neutral Network (ANN) in concurrent diagnosis of diabetes and hypertension. Methods: This cross-sectional study was performed with 12000 ...
متن کاملPredicting all-cause risk of 30-day hospital readmission using artificial neural networks
Avoidable hospital readmissions not only contribute to the high costs of healthcare in the US, but also have an impact on the quality of care for patients. Large scale adoption of Electronic Health Records (EHR) has created the opportunity to proactively identify patients with high risk of hospital readmission, and apply effective interventions to mitigate that risk. To that end, in the past, n...
متن کاملartificial neural networks versus bivariate logistic regression in prediction diagnosis of patients with hypertension and diabetes
background: diabetes and hypertension are important non-communicable diseases and their prevalence is important for health authorities. the aim of this study was to determine the predictive precision of the bivariate logistic regression (lr) and artificial neutral network (ann) in concurrent diagnosis of diabetes and hypertension. methods: this cross-sectional study was performed with 12000 ira...
متن کاملArtificial neural networks versus bivariate logistic regression in prediction diagnosis of patients with hypertension and diabetes
BACKGROUND Diabetes and hypertension are important non-communicable diseases and their prevalence is important for health authorities. The aim of this study was to determine the predictive precision of the bivariate Logistic Regression (LR) and Artificial Neutral Network (ANN) in concurrent diagnosis of diabetes and hypertension. METHODS This cross-sectional study was performed with 12000 Ira...
متن کاملPrediction and cross-validation of neural networks versus logistic regression: using hepatic disorders as an example.
The authors developed and cross-validated prediction models for newly diagnosed cases of liver disorders by using logistic regression and neural networks. Computerized files of health care encounters from the Fallon Community Health Plan were used to identify 1,674 subjects who had had liver-related health services between July 1, 1992, and June 30, 1993. A total of 219 subjects were confirmed ...
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ژورنال
عنوان ژورنال: Scientific Reports
سال: 2019
ISSN: 2045-2322
DOI: 10.1038/s41598-019-45685-z