PredictMD by Atyang

Inspiration

Inspiration came from realizing the unmet need for personalized care for Muscular Dystrophy patients in resource-constrained settings. The increasing accessibility of wearable devices and smartphones sparked the vision of creating a machine learning-based model to personalize management of Muscular Dystrophy patient.

What it does

This project harnesses power of Machine Learning to create personalized exercise prescriptions.

How we built it

Problem definition was the first step followed by identifying the key data types needed. Model selection and development using Python language was done. Cross validation was done to ensure model robustness. Performance of the machine learning model was assessed using metrics like accuracy, precision and recall.

Challenges we ran into

limited existing data on Muscular Dystrophy in Kenya which was our study site. Collecting comprehensive patient data is difficult

Accomplishments that we're proud of

lt is a great accomplishment pioneering Machine Learning based model for personalized exercise recommendations in Muscular Dystrophy patients in Kenya.

What we learned

This project inspired learning the importance of patient-centered design approach in exercise recommendations for Muscular Dystrophy patients.

What's next for PredictMD by Atyang

We see potential in adapting our model for other neuromuscular disorders and even extending it to preventive care, predicting and preventing secondary complications in Muscular Dystrophy. As we advance, we'll implement enhanced privacy measures and ensure compliance with evolving AI/ML regulations in healthcare. We aim to conduct multi-center trials across Africa and collaborate with international MD research centers.

Built With

• python