Veronika Cheplygina at Spring Meeting 2022: Deep Understanding

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Responsible research practices for machine learning in medical imaging

by Dr. Veronika Cheplygina (IT university of Copenhagen)

Medical imaging is an important research field with many opportunities for improving patients’ health. However, there are a number of challenges that are slowing down the progress of the field as a whole, such as optimizing for publication. In this talk I discuss several problems which occur when we as researchers make decisions about choosing datasets, methods, evaluation metrics, and publication strategies. I will also discuss various initiatives that have already been started to counteract these problems, and provide some more general recommendations on how to further these address problems in the future.

We have three more speakers at this event.

• Bart ter Haar Romenij (TU/e), our society president will give his farewell lecture on something quite special: understanding deep learning from first principles and the human visual system. To support the credibility: all will be explained with life coding.

• Alex Frangi (Leeds Univ.), an outstanding computer vision researcher from England tells about research at the crossroads of image analysis and modeling with emphasis on machine learning.

• Efstratios Gavves(UvA), will teach us on the so crucial (and rewarding) dynamics of temporal machine learning.

May 2022
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