Bridge the gap between patient experience and clinical understanding through comprehensive, secure, and accessible pain tracking technology. A privacy-first, offline-capable PWA for chronic pain management.

A data-driven clinical decision support tool demonstrating the end-to-end deployment of a machine learning pipeline using Python, PyCaret, and Streamlit.

SQL + Power BI + Excel analytics system built on public CMS hospital data. Tracks 30-day readmission rates, HCAHPS patient satisfaction, and clinical quality indicators across 4,800+ U.S. hospitals — with benchmarking, trend analysis, and operational efficiency reporting across three dashboard pages.

Hospital length-of-stay prediction for NY hospitals. Risk-stratify patients at admission for proactive discharge planning. Built on SPARCS 2024 data.

End‑to‑end reproducible data pipeline for clinical records and health analytics.

This is an end-to-end healthcare analytics platform designed for processing and analyzing patient data at scale.

Supervised machine learning pipeline for heart disease risk prediction using clinical data, achieving strong accuracy with interpretable feature analysis

An end-to-end clinical data engine for the 1Sage Navigator. Transforms raw FHIR patient bundles into a stratified Gold Layer using a Medallion Architecture. Includes Kaplan-Meier survival analysis and propensity score matching for population health insights.

A Power BI dashboard for analyzing the systemic impact of smoking on patient organ health built from synthetic patient data to visualize how smoking behavior correlated with organ damage across heart, lungs, liver, and kidneys.

End-to-end machine learning and explainability pipeline for predicting 30-day hospital readmission risk using synthetic EHR data.

HIPAA-aware healthcare data platform with FHIR ingestion, patient matching, provider workflows, dbt analytics, and governed AI queries.