AI-powered air quality monitoring platform that analyzes PM2.5 exposure and health conditions to provide personalized health risk alerts and recommendations.

A real-time ML system that monitors animal vitals and behavior to predict health risks and trigger an automated precaution alert system.

Semi-supervised learning using positive and unlabeled learning for hypertension risk prediction.

End-to-end ML pipeline to classify patient health risk (Healthy vs. High Risk) using EDA, Logistic Regression, Random Forest, and XGBoost — with feature importance analysis and ROC-AUC evaluation.