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AIMI Journal Club: Gender Imbalance In Medical Imaging Datasets Produces Biased Classifiers for Computer-aided Diagnosis - Enzo Ferrante

Event Details:

Thursday, August 13, 2020
3:00pm - 4:00pm PDT

via Zoom

The live event is for the Stanford community. The recorded presentation is available here for everyone to view.

We will be discussing the following article with the author:

Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis

Agostina J. Larrazabal, Nicolás Nieto,  View ORCID ProfileVictoria Peterson,  View ORCID ProfileDiego H. Milone, and  View ORCID ProfileEnzo Ferrante

PNAS June 9, 2020 117 (23) 12592-12594; first published May 26, 2020 https://doi.org/10.1073/pnas.1919012117

About:
Enzo completed his PhD in Computer Sciences at Université Paris-Saclay (CentraleSupeléc / INRIA) in Paris, and worked as postdoctoral researcher at Imperial College London (BioMedIA Lab), in the UK. He returned to Argentina in 2017, where he holds a research scientist position from the Argentina's National Research Council (CONICET) and a lecturer position at Universidad Nacional del Litoral. He leads the Machine Learning for Biomedical Image Computing research line in the Research Institute for Signals, Systems and Computational Intelligence, sinc(i). His research interests span both artificial intelligence and biomedical image analysis, with focus on deep learning methods. Personal Website: https://eferrante.github.io/

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