Analysis toolkit for clinical and genetic data.

Statistical analysis of a Phase III clinical trial dataset to evaluate diabetes medication effectiveness and safety.

Classifying clinical trials by trustworthiness using machine learning- quality control

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

Healthcare AI project analyzing migraine treatment outcomes using longitudinal statistical models in R.

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.

Clinical data analytics portfolio focused on medication use, safety, and access in Canadian healthcare. Includes Python, SQL, and data visualization projects using real drug and public health datasets.

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

Predictive healthcare analytics project using SPSS and Tableau to identify BP control failure risk factors and evaluate antihypertensive treatment effectiveness.

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.

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.

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

SQL-based analysis of hospital operations, patient trends, and financial performance.

Healthcare machine learning project that predicts heart disease risk using patient clinical data, exploratory analysis, and multiple classification algorithms to support early diagnosis and data-driven medical decision-making.

Bachelor thesis on adherence analysis in long-term digital monitoring of symptoms in patients with schizophrenia.

🩺 Medsense AI (Medical Report Summarizer) is an AI-powered healthcare platform that transforms complex medical reports into simple, patient-friendly summaries. The system uses OCR, natural language processing, & AI-driven analysis to extract information from PDFs and medical images, generate structured insights, & help patients better understading

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).

This project applies pharmacovigilance signal detection to 6,000 FDA adverse event reports across five pharmaceutical products to identify elevated drug reaction signals, demographic risk profiles and mortality trends supporting regulatory safety monitoring decisions.

Alzheimer’s Disease Prediction is a classification-based machine learning project aimed at predicting the likelihood of Alzheimer’s disease in elderly individuals using clinical and demographic features.

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