Abstract: Logistic regression is a fundamental and widely used statistical method for modeling binary outcomes based on covariates. However, the presence of missing data, particularly in settings ...

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 ...

Marketing campaigns play a crucial role in driving business growth, particularly in the financial industry. Within the context of telemarketing, which involves contacting customers remotely through ...

Introduction: Machine learning (ML) methods are promising and scalable alternatives for propensity score (PS) estimation, but their comparative performance in disease risk score (DRS) estimation ...