Projects
Our Projects
Latest Works
Early Alzheimer’s Detection Using Deep Neural Networks
This project uses deep learning to detect early signs of Alzheimer’s Disease from brain MRI scans. We trained a ResNet-50 model on the public OASIS dataset to classify patients as non-demented, mildly demented, or fully demented. The AI looks for small changes in brain structure and can predict Alzheimer’s with high accuracy.
This tool helps doctors diagnose the disease early, plan treatment, and improve patient care. It’s fast, easy to use, and non-invasive—making it useful for neurologists, radiologists, and healthcare providers. The project shows how AI can improve medical imaging and support early detection of brain diseases.
Analyzing the Co-Relation Between Diabetes and Parkinson’s
This project uses machine learning to predict the risk of Parkinson’s Disease based on health data linked to Type 2 Diabetes (T2DM). It looks at common factors like insulin resistance, inflammation, and oxidative stress to make accurate predictions with 92% accuracy. A user-friendly web app lets people enter their health details and see their risk across four possible health conditions.
This AI tool helps with early detection, better prevention, and personalized care. It’s easy to use, clinically useful, and fits well into digital health, AI in healthcare, and public health monitoring platforms.
Sign Language Translation System
Real-Time Sign Language Detection using Machine Learning is an AI-based project built to improve communication for the hearing-impaired. Developed using Python, TensorFlow, MediaPipe, and OpenCV, it detects hand gestures in real-time and translates them into text. The system uses an LSTM deep learning model trained on sequential gesture data for accurate recognition. With low latency and high precision, it showcases a practical application of computer vision and time-series analysis. This project aligns with trending domains like assistive technology, gesture recognition, and human-computer interaction. It demonstrates core concepts in deep learning, natural language processing, and real-time application development.