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.

The project uses natural language processing and information retrieval to create an interactive system for user queries on a collection of PDFs. It involves loading, segmenting, and embedding PDFs with a Hugging Face model, utilizing Pinecone for efficient similarity searches

Code for IJCV-From Small to Large: In-Context Learning as a New Paradigm for Domain Generalization

video capsule endoscopy abnormality classification for capsule vision 2024 challenge

🌐 A full-stack telehealth platform enabling virtual consultations, real-time symptom prediction via AI, and chatbot-assisted triage — built with React, Node.js, and Python.

Project COLON-X (Shaping the neXt frontier in intelligent COLONoscopy)

A TSX-based wellness and cycle care tracking app with mood journal, symptom tracker, and AI assistant.

Official PyTorch Implementation of paper 'Edge-Based Graph Neural Networks for Cell-Graph Modeling and Prediction'

A curated list of tools, frameworks, applications, datasets, and resources for AI in Healthcare.

💻🔒 A local-first full-stack app to analyze medical PDFs with an AI model (Apollo2-2B), ensuring privacy & patient-friendly insights — no external APIs or cloud involved.

AI Toolkit for Healthcare Imaging in Keras 3

Real-ESRGAN model deployed on Android using NCNN (C++/JNI) and ExecuTorch (Java) for real-time image super-resolution in dermatology, with reproducible benchmarking (PSNR, SSIM, MSE, LPIPS).

Binary classification of breast cancer using PyTorch. Used StandardScaler, LabelEncoder, Dataset, DataLoader, custom nn.Module model, BCELoss, and SGD. Focused on implementing a complete training pipeline, not optimizing accuracy.

Smart solution addressing PTSD, security, and post-service instability for military personnel

ChannelMAE is a combination of MAE and ChannelViT

Detection of presence or absence of pneumonia in chest x-ray images using a CNN deep learning architecture

Health Information Website with Chatbot Source Code

A multimodal AI-powered virtual doctor that leverages voice and vision technologies to provide preliminary medical consultations. Built with Python, incorporating speech recognition, text-to-speech, image analysis, and a Gradio interface for seamless user interaction.

The medical chatbot uses AI and NLP to analyze user symptoms, extract key medical details, and recommend the appropriate doctor department. It also generates a concise medical report summarizing the symptoms and suggested consultation

AI-powered medical assistant chatbot for symptom checking, disease prediction, severity analysis, and self-care guidance