Balancing Innovation and Sustainability: A Pragmatic Approach to Environmental Responsibility in Deep Learning for Pathology

This research delves into a pressing concern within pathology – the significant carbon dioxide equivalent (CO2eq) emissions associated with integrating deep learning. This environmental impact poses a potential obstacle to the widespread adoption of deep learning in medical applications, prompting an urgent need for sustainable practices. As the world increasingly relies on technological advancements in […]

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