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

Exploratory data analysis on clinical operations using MIMIC-IV dataset, focusing on ICU utilization, vitals monitoring intensity, length of hospital stay, and in-hospital mortality.

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.

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

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.

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

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).

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