Researchers develop a new AI model that achieves 95% accuracy in predicting various diseases, paving the way for proactive and personalized healthcare.
Researchers at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology have been busy cooking up something exciting in the world of AI and healthcare. They’ve just unveiled a new ensemble feature selection model that’s like a superhero team for disease prediction, combining the powers of statistical, deep, and optimally selected features.
At the heart of this model is the SEV-EB algorithm, a fancy new way to pick out the most important features from a mountain of health data.
But that’s not all. The researchers also threw in HSC-AttentionNet, a neural network for spotting patterns and trends in health data over time.
When they put this model to the test, it blew the competition out of the water. It achieved a whopping 95% accuracy and 94% F1-score in predicting various diseases.
This breakthrough could be a game-changer for healthcare. Imagine getting diagnosed and treated for diseases before you even show symptoms. That’s the kind of promise this model holds.
The researchers are already planning to add even more superpowers to their model, like incorporating genomic and environmental data.
The research paper can be downloaded here (PDF).
