Overview / Usage

Inspiration :

The inspiration behind CureQuest came from the realization that existing healthcare machine learning models have limitations in efficiently predicting multiple diseases and optimizing algorithms for different hardware architectures. The team recognized the need for a comprehensive system that could accurately predict various diseases while leveraging advanced hardware optimization tools.

What it does?

CureQuest is a groundbreaking AI-powered medical platform that enables patients to detect six critical diseases from the comfort of their homes, using just a few clicks. Leveraging the power of Intel® oneAPI Tools, the platform integrates advanced machine learning algorithms and deep neural networks to provide accurate test results for Brain Tumor Detection, Breast Cancer Detection, Alzheimer's Detection, Diabetes Detection, Pneumonia Detection, and Heart Disease Detection.

Methodology / Approach

** How we built it?**

• To build CureQuest, we utilized Intel® oneAPI Tools, specifically the Intel® AI Analytics Toolkit (AI Kit), which played a crucial role in optimizing our machine learning models for Intel architecture.
• By integrating oneAPI into scikit-learn and enhancing deep learning APIs like Keras, our team achieved improved performance and efficiency.
• We employed pre-trained convolutional neural networks (CNNs) for feature extraction and developed custom-made CNNs for disease detection, ensuring accurate predictions.

Technologies Used

What we learnt?

• We are immensely proud of creating CureQuest, a cutting-edge medical solution that addresses the inefficiencies of traditional healthcare models. Through the seamless integration of Intel® oneAPI Tools, our platform demonstrates remarkable accuracy in disease detection, achieving results ranging from 66.8% to an impressive 100%. Moreover, offering six critical disease detections under one comprehensive platform sets CureQuest apart, providing immense value and convenience to patients.
• During the development of CureQuest, we learned the importance of leveraging advanced AI tools like Intel® oneAPI to optimize machine learning models effectively. The integration of oneAPI into our platform significantly improved the performance and efficiency of our algorithms on Intel architecture. Additionally, we gained insights into disease detection techniques using various algorithms like VGG-16, Random Forest, custom-made CNNs, and XGBoost, which contributed to our overall success.

Documents and Presentations

Repository

https://github.com/shruthi2608/CureQuest/

Other links

• CureQuest-YouTube

Collaborators