Classifying clinical trials by trustworthiness using machine learning- quality control

Analysis toolkit for clinical and genetic data.

Implement logistic regression using Python and scikit-learn to classify malignant vs. benign tumours from the Breast Cancer Wisconsin (Diagnostic) dataset

Healthcare data analytics project analysing hospital encounter data to evaluate clinical utilisation, length of stay, readmissions, payer exposure, and mortality trends.

This project focuses on developing a non-invasive prediction model that can serve as an alternative to invasive liver biopsies for assessing liver fibrosis and its level of progression in patients with Hepatitis C Virus (HCV).

A data science analysis of therapeutic game performance in physical rehabilitation, using score-per-minute metrics and game difficulty mapping.

A machine learning project focused on predicting chronic kidney disease (CKD) stages and performing survival analysis using clinical biomarkers. It utilizes the Kaplan-Meier estimator to analyze patient progression and visualize survival probabilities, offering insights into CKD management.

This project predicts brain stroke risk using machine learning by analyzing medical and lifestyle factors. It includes data preprocessing, model training, and a simple web interface for real-time predictions. Designed for learning, research, and healthcare analytics, it demonstrates practical ML applications in disease-risk assessment.

Detect HPV as the primary cause of Head and Neck Carcinoma.