PawSome AI, an innovative application designed to assist pet owners with various tasks such as disease and breed detection, pet care chatbot, and prescription analysis

Breast cancer histopathology image segmentation using U-Net. This repository implements U-Net for accurate segmentation of cancerous regions. It includes data augmentation, mixed precision training, checkpointing, and evaluation metrics like Dice score to improve model performance.

MedFuse is a scalable tool for multi-modal clinical case retrieval, enabling diagnostic ease, triage readiness, and medical staff training

A lightweight expert-system framework for modeling and testing medical diagnostic rules, with multiple approaches.

This project uses a synthetic healthcare dataset to predict patient test results ("Normal," "Abnormal," or "Inconclusive") using machine learning. It employs ensemble methods such as Bagging, Random Forest, Boosting, and Stacking classifiers with feature engineering and preprocessing.

Mealzy Health is a health and wellness companion powered by AI, designed to help users make smarter food choices, monitor their nutritional intake, and build sustainable habits

This project predicts lung cancer risks using machine learning models like Random Forest, Logistic Regression, and SVM. It analyzes patient data with features such as age, smoking habits, and symptoms. Data preprocessing, visualization, and performance evaluation ensure accurate predictions for early diagnosis.

This project aims to detect pneumonia from chest X-ray images using a Convolutional Neural Network (CNN). The model is trained on a dataset of chest X-ray images and evaluated for its performance. The project is ongoing, and I aim to fine-tune the model in the future. If you are seeing this, it means I am still working on the project.

Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials. CNNs for Medical Image Classification leverages deep learning to analyze medical images, detect diseases, and assist doctors in accurate and faster diagnosis.

RareLink is the Grand Champion🥇 for Genomic Diagnostics track at Harvard Rare Disease 2025.

Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials. Deep Learning for Protein Structure Prediction leverages neural networks to model protein folding and predict 3D structures, enabling faster biological research and improved drug discovery processes.

A list of my deep learning projects utilizing packages like tensorflow, openAi, GPT2LMHeadModel, gym, pandas

This project detects the chest disease with AI model.

Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials. Deep Learning in Drug Discovery leverages neural networks to analyze molecular and biological data, predict drug-target interactions, and speed up the development of effective and safe medicines.

Skin Diseases Detection using MNIST dataset and CNN

A deep learning-based approach for automatic detection of brain tumors from magnetic resonance imaging (MRI) scans. Brain Tumor Detection using Deep Learning Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials

This project utilizes machine learning algorithms to predict the likelihood of diabetes based on various risk factors. Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials

This repository contains an end-to-end workflow for multi-class brain MRI tumor classification implemented in MRIBrainTumorDetection.ipynb. It uses TensorFlow/Keras to build a baseline CNN and a VGG16-based transfer learning model to classify scans into four classes (glioma, meningioma, pituitary, no tumor).

How can Artificial Intelligence (AI) and Big Data improve the tracking, prediction, and response to Emerging Infectious Diseases (EIDs), especially in resource-limited settings?