12 Jul 2019

Localizing Pneumonia from Chest X-rays with Potentially Multiple Abnormalities

In a new paper accepted early to the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), a team of reseachers from Mila, Imagia, and Simon Fraser University have proposed a weakly supervised interpretable deep model called InfoMask, which localizes a target disease from chest X-rays with multiple diagnostic labels by learning to mask out irrelevant input variables.

InfoMask is a joint work by Saeid Asgari, Mohammad Havaei, Tess Berthier, Francis Dutil, Lisa Di Jorio, Ghassan Hamarneh, and Yoshua Bengio.


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Mila goes virtual

Starting March 16, 2020, Mila shifts its activities to virtual platforms in order to minimize COVID-19 diffusion.

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