This project is dedicated to the comparative analysis of medical visits (27,000+ records) using three different technology stacks. The main goal is to validate data and calculate key metrics of a medical facility's performance.

End-to-end healthcare analytics project using synthetic patient data. Performs exploratory analysis, feature engineering, and multi-class machine learning to predict medical test outcomes (Normal, Abnormal, Inconclusive) while generating interpretable insights for healthcare decision support.

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SQL analysis of Alzheimer's biomarkers using ADNI data

Interactive Power BI dashboard analysing hospital admissions, emergency vs planned admissions, wait times, and speciality performance using healthcare data.

The project aims to predict the likelihood of heart disease in individuals based on medical data using various machine learning algorithms. The project involves data preprocessing, feature selection, model training, and evaluation. The goal is to create a predictive model that assists healthcare professionals in diagnosing heart conditions

This project explores a real-world healthcare dataset using Python and pandas. We loaded, cleaned, and analyzed the data, then used charts to uncover key patterns.

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