44 Machine Learning Workshop at MICCAI research , ” Thomas tells us. “ The second track is more applied. We want to find applications that have, for instance, found an interesting parcellation of the brain, sub-stratification of a disease, or made some clinically relevant conceptual changes . ” We are yet to understand our brains fully, and there is still much to learn and discover in neuroimaging . Vinod tells us he has been investigating the brain using a combination of high-resolution MRI and machine learning. He is fascinated by how it works. “ There are many clinical applications that are in dire need of new methods to understand the brain, different The Machine Learning in Clinical Neuroimaging (MLCN) workshop was established in 2018 and remains as relevant as ever. Over the last five editions, it has seen a range of exciting discoveries and engaging talks. One standout keynote was given by a friend of this magazine, Jorge Cardoso , in 2020, when MONAI was in active development. The workshop aims to bridge the gap between machine learning and clinically applied research. With that aim in mind, it is divided into two tracks. “ The first track is about the development of novel machine learning technology , with an eye on clinical utility in the context of brain imaging and neuroscientific MACHINE LEARNING IN CLINICAL NEUROIMAGING (MLCN) Thomas Wolfers is the Group Leader of the Laboratory for Mental Health MappingattheUniversityofTübingeninGermany.NichaDvornekisanAssistant Professor at Yale University in the Department of Radiology & Biomedical Imaging and the Department of Biomedical Engineering. Vinod Kumar is a Postdoc at the Max Planck Institute for Biological Cybernetics Tübingen. They speak to us today as co-organizers of a fascinating workshop later this year at MICCAI 2023 in Vancouver.