Better diagnosing diseases with the help of AI

Researchers improve the trustworthiness of medical imaging diagnoses with an innovative three-stage system powered by AI

By: Media Relations

An interdisciplinary team of researchers at the University of Waterloo has developed a more trustworthy method to diagnose diseases such as COVID-19, pneumonia, and melanoma using artificial intelligence (AI) tools.

Waterloo engineering professor Alexander Wong teamed up with other researchers from the university, McGill University, and the National Research Council of Canada to develop a new method to support doctors by enhancing computer-aided diagnosis through deep learning.

The researchers created a system they’ve dubbed Trustworthy Deep Learning Framework for Medical Image Analysis (TRUDLMIA), which leverages the power of supervised and self-supervised AI learning that aims to pave the way for advancements in high-performing and trustworthy healthcare models.

“Models employing the TRUDLMIA approach outperform existing ones in various tasks, excelling in COVID-19, pneumonia, and melanoma diagnosis, surpassing models specifically designed for those tasks in terms of both performance and trust,” said project lead Dr. Wong, the Canada Research Chair in Medical Imaging and Artificial Intelligence. “The proposed system is undergoing further development to address future pandemics and syndromes, including long-term effects associated with COVID-19.”

To read the full article click here.