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Explore a cutting-edge modeling framework based on Capsule Networks, known as COVID-CAPS, designed to identify COVID-19 cases from X-ray images. In this 20-minute conference talk presented at the Toronto Machine Learning Series (TMLS), learn how this innovative approach effectively handles small datasets, a crucial advantage given the sudden and rapid emergence of COVID-19. Discover the advantages of COVID-CAPS over previous CNN-based models and gain insights into its performance using X-ray image datasets. Delve into the potential of Capsule Networks in medical imaging and their application in addressing urgent healthcare challenges.
