Abstract: This study utilizes decision tree and logistic regression models to explore the factors contributing to medical claim denials and identify areas for improvement. We adapt undersampling ...

A complete implementation of Logistic Regression with Gradient Descent optimization from scratch using only NumPy, demonstrating mathematical foundations of binary classification for diabetes ...

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...

Background and objectives: Carotid atherosclerosis (CAS) is increasingly prevalent among hypertensive patients. This study aims to develop a predictive nomogram for CAS in hypertensive population.

ABSTRACT: This paper aims to investigate the effectiveness of logistic regression and discriminant analysis in predicting diabetes in patients using a diabetes dataset. Additionally, the paper ...

This set of notebooks enables the analysis of comorbidities associated with male infertility using structured EHR data. First, we identified nonoverlapping patients with male infertility and patients ...

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you understand ...

1 Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan 2 RIKEN Center for Advanced Intelligence Project, Tokyo, Japan In recent years, a learning method for classifiers using ...