Machine reasoning in histopathologic image analysis

After the talk, at 6.45 pm, everyone is welcome to join for a virtual "pub chat" with Prof. Phedias Diamandis. Details on how to join the talk and the informal "pub chat" will be released via our mailing list (info on how to subscribe on

Deep learning is an emerging computational approach inspired by the human brain’s neural connectivity that has transformed machine-based image analysis. By using histopathology as a model of an expert-level pattern recognition exercise, we explore the ability for humans to teach machines to learn and mimic image-recognition and decision making. Moreover, these models also allow exploration into the ability for computers to independently learn salient histological patterns and complex ontological relationships that parallel biological and expert knowledge without the need for explicit direction or supervision. Deciphering the overlap between human and unsupervised machine reasoning may aid in eliminating biases and improving automation and accountability for artificial intelligence-assisted vision tasks and decision-making.