Abstract: This paper's primary goal is to use machine learning techniques, specifically Logistic Regression and Decision Trees, to identify bogus news on social media. An innovative logistic model is ...

Abstract: Body Mass Index is a main indicator for assessing weight related health risks and classifying individuals listed as underweight, normal, overweight or obese. Accurate prediction of BMI ...

heart-disease-logistic-regression/ ├── data/ # dataset (heart_disease_uci.csv) ├── src/ # source code │ ├── heart_disease_logistic_regression.py │ └── plot_results.py ├── figures/ # generated plots ...

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 ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

This cross-sectional study investigates the interplay of lifestyle, behavioral, and psychosocial factors in predicting depressive symptoms among Chinese college students (N=508) using binary logistic ...

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 ...

ABSTRACT: Road traffic accidents are one of the global safety and socioeconomic challenges. According to WHO (2024), it has caused over 1.19 million annual fatalities. It is also projected to cause ...