APC 2018: A School for AI Students Studying Pathology

Session: Artificial Intelligence: What you need to know and its impact on the future of pathology

In this talk, I discuss our vision for an AI School of Pathology: Where AI systems are trained to understand and interpret pathology in much the same way that human students are taught.

By recasting the problem of AI training as one of pedagogy, we can start to understand how these systems learn, what they are actually learning, and why they make mistakes. We can also learn ways to efficiently train a classifier to understand complex class spaces.


About

I am Assistant Professor of Pathology and Anatomical Sciences, Biomedical Engineering, and Biomedical Informatics at the University at Buffalo, SUNY. My lab develops computational tools for medical data, with a focus on imaging, machine learning, and artificial intelligence.

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