Comparing Logistic Regression and Artificial Neural Network Models for Analyzing Medicare Utilization and Costs Among Older Adults

Both logistic regression and ANN models effectively predict health care utilization and high-risk outcomes among older adults using structured Medicare data. Logistic regression offers interpretability and robust predictive power, whereas ANN models may provide additional value as healthcare datasets grow increasingly complex and comprehensive.

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Publication Details

Journal
Medical Care
Published
2026-03-02
DOI
https://doi.org/10.1097/mlr.0000000000002305
Primary Topic
Heart Failure Treatment and Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Comparing Logistic Regression and Artificial Neural Network Models for Analyzing Medicare Utilization and Costs Among Older Adults

Min Qi Wang, Jie Chen, Seyeon Jang
Medical Care
Heart Failure Treatment and Management
article

Comparing Logistic Regression and Artificial Neural Network Models for Analyzing Medicare Utilization and Costs Among Older Adults

Min Qi Wang, Jie Chen, Seyeon Jang
article en

Abstract

Both logistic regression and ANN models effectively predict health care utilization and high-risk outcomes among older adults using structured Medicare data. Logistic regression offers interpretability and robust predictive power, whereas ANN models may provide additional value as healthcare datasets grow increasingly complex and comprehensive.

Medical Care
Public Health Department (IN), Integrated Optoelectronics (Norway) (NO), University of Maryland, College Park (US)
No poverty
Openalex Percentile: Top 43%
Heart Failure Treatment and Management
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