New MIDL 2022 short paper on strategies for meta-learning with diverse tasks

Last updated on Nov 3, 2022

Stefano Woerner’s paper on “Strategies for Meta-Learning with Diverse Tasks” got accepted to the MIDL 2022 short paper track. Meta-learning research is typically evaluated on very homogenous toy tasks and it is unclear how directly this technology is applicable to much more diverse medical imaging tasks. In this work, Stefano does a first step in the direction of answering this question.

Resources: Paper | Short Project Description | Video

Machine Learning in Medical Image Analysis
Machine Learning in Medical Image Analysis
Bridging the gap between AI and clinical practice