Artificial intelligence is rapidly changing the job market, automating jobs across industries. Therefore, in such a scenario, upskilling oneself in industry-relevant AI skills becomes even more ...

Abstract: This paper describes a machine learning-based analysis of crop yield prediction across the states of India using a Logistic Regression and Random Forest classifiers. The analysis relied on ...

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

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 ...

Department of Industrial and Systems Engineering, North Carolina A & T State University, Greensboro, NC, USA. According to the Centers for Disease Control and Prevention (CDC), diabetes is a long-term ...

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: Pneumonia, a severe respiratory infection, remains a leading global cause of death, particularly among vulnerable populations such as children and the elderly, underscoring the importance of ...

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 ...

In standard ER analyses, exposure metrics are derived using individual empirical Bayes estimates from a developed population pharmacokinetic (PopPK) model. For each subject, the PopPK model is then ...