AI Synergies


Emmeke Veltmeijer

PhD student

Integrating clinically-relevant features into skin lesion classification

To increase both the accuracy and the explainability of computer-aided diagnosis systems, a multi-task network was built to perform skin lesion classification. Clinically-relevant features were provided as secondary output during training, next to the ground truth classification. 

These clinically-relevant features were either the absence/presence of certain malignancy signs within the skin lesion, or segmentation masks of them. The former did not significantly increase the performance, whereas the latter did.


After receiving a bachelor’s degree in Psychobiology, Emmeke went on to pursue a master’s degree in Artificial Intelligence, both at the University of Amsterdam. After graduating last August, she started a PhD at the Vrije Universiteit Amsterdam, on the topic of prediction of crowd dynamics.


Syrah room
Research presentations AI
Day 2 - Nov 7th

Brewery of Ideas

AI Synergies is organized by VUB/ULB, BNVKI and Brewery of Ideas.

More info about our events