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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
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.
💻🔒 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.
🏥 DICOM Flask App – AI-Powered Lesion Detection A Flask-based web app for uploading, processing, and analyzing DICOM medical images. Uses DeepLesion (Faster R-CNN) for lesion detection and ResNet50 for classification. Features a multi-tab UI with sidebar navigation. A sample DICOM file is included for testing!
CardioGuard is an AI-powered cardiac health monitoring and alert system that detects early signs of cardiac arrest using real-time sensor data and machine learning, instantly notifying emergency contacts and healthcare providers.
HealthCare Assistant is an AI-powered healthcare companion using Streamlit and Groq, providing symptom analysis, medication guidance, health record management, and wellness recommendations.
The "Nutritionist-Generative-AI-Doctor-using-Google-Gemini-Pro-Vision" project leverages Google Gemini Pro Vision to create an AI-driven nutritionist and doctor that offers personalized health advice. It uses generative AI to analyze user data and provide tailored recommendations for diet and well-being.
AI-Powered Eye Disease Detection Web App An intelligent retina image classification system built using deep learning (VGG16), TensorFlow, and Flask. This open-source project helps detect common eye diseases like Cataract, Diabetic Retinopathy, and Glaucoma, and also identifies uncertain cases as Unknown.
An AI-powered gamified rehabilitation and wellness platform helping users recover from mental health, addiction, and diet-related challenges through personalized tasks, therapy tracking, and predictive analytics.