Where AI Meets Biology
We aim to incorporate Artificial Intelligence to pioneer advancements that transform healthcare and redefine possibilities for a healthier and more sustainable future
Our Goals
Research
→ Utilizing AI algorithms for the analysis of large-scale neurological datasets.
→ Developing predictive models to identify patterns and early signs of neurological diseases.
→ Implementing machine learning techniques to predict disease progression based on patient data.
Development
→ Develop Image Recognition Software using AI-powered algorithms for interpreting medical imaging data
→ Drug development through AI analysis of vast datasets.
→ Large scale AI bot to monitor individuals health and assist in day to day tasks
Project 1: Brain Tumor AI Recognition
This project harnesses the power of artificial intelligence to detect brain tumors in various brain scan images. Through the use of Python and other libraries such as NumPy, TensorFlow, and PyTorch we developed a machine learning algorithm that trained on a large dataset of brain scans with tumors and without tumors. The data was initially transformed and processed into NumPy arrays where the visual images were turned into large matrices of values representing the RGB numbers of every pixel in an image. Then through the architecture of a Convolutional Neural Network, this data passes through a series of layers to eventually return a result of tumor or healthy. This model then learned through continuous forward and backward propagation of the data through the Neural Network and gained the ability to recognize images with a tumor and ones without at a 100% accuracy.
Project 2: MedTrak Application
→ Medicine Tracker & Reminder Application
→ Allows patients to keep track of their medications and alerts patients when to take their medications