This repository houses machine learning models and pipelines for predicting various diseases, coupled with an integration with a Large Language Model for Diet and Food Recommendation. Each disease prediction task has its dedicated directory structure to maintain organization and modularity.

Built a regression model that predicts the expected days of hospitalization time and an uncertainty range estimation.

Built an activity-aware pulse rate estimation using PPG and Accelerometer sensors.

Gene Regulatory Network Inference

Reinforcement Learning for policy-making for epidemics (EpiPolicy https://youtu.be/JDYb4_coAf4)

Assisting a radiologist in classifying a given chest x-ray for the presence or absence of pneumonia using Deep Learning.

Approximated missing values in noisy, heterogeneous electronic health records by low rank modeling.

Created a chatbot using Google’s Generative AI to assist parents of autistic children with concise answers on therapy, communication, sensory needs, and future planning. Its user-friendly design provides practical support, empowering families to better care for their children.

The project focuses on building machine learning models for dental image classification and detection. Using CNN for image classification and YOLOv5 for object detection, the models aim to identify various dental conditions from medical images. The repository contains the data preprocessing pipeline, model training, and evaluation methods.

[ACIIDS 2024] DiabetesNet: A Deep Learning Approach to Diabetes Diagnosis

Error-Correcting Code for On-Patient Medical Record - Code for Deep Learning-assisted On-patient Medical Record and mRNA Therapeutics Delivery using Microneedles (Nature Materials 2025)

Created a chatbot using Google’s Generative AI to assist parents of autistic children with concise answers on therapy, communication, sensory needs, and future planning. Its user-friendly design provides practical support, empowering families to better care for their children.