clinical-data-analysis

Analysis toolkit for clinical and genetic data.

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

Classifying clinical trials by trustworthiness using machine learning- quality control

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.

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

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

SQL Analysis for HCV patients

Advanced survival analysis using ASA‑aligned methods, including Cox PH modeling, Kaplan–Meier curves, hazard estimation, diagnostics, and reproducible time‑to‑event workflows. Built as a professional portfolio project demonstrating modern statistical survival modeling.

Investigates how age, gender, BMI, and hypertension relate to pulse, blood pressure, and glucose using MANOVA, MANCOVA, and multivariate regression. Includes data cleaning, Box‑Cox transforms, model comparison, and post‑hoc analyses to identify key health predictors.

Multiple Correspondence Analysis (MCA) with Benzécri correction on the Rotterdam Breast Cancer dataset (n=2,982) — uncovers 3 clinical patient profiles linking age, tumor grade, and treatment strategy to recurrence risk.

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.

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

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

Automated Python pipeline for cleaning, analyzing, and visualizing ophthalmic surgical outcome data.

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.

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

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.