Computer Vision News - May 2023

46 Machine Learning Workshop at MICCAI at this stage in their career. All agree that it is one of the most fascinating organs of the human body, and largely still a mystery, even though it realizes many of the functions that make us human. “ We operate our consciousness and experience emotions through the brain, ” Vinod muses. “ It’s why we’re enjoying this beautiful conversation. You’re curious, and we’re also curious to talk get these new techniques adopted by clinicians to improve both analysis and clinical workflow? ” The team hopes the workshop will ultimately lead to robust machine learning algorithms that can handle messy clinical practice data with the same ease as large- scale off-the-shelf or consortia datasets with well-resourced acquisition protocols. Mental and neurological disorders are often heterogeneous, and identifying individual differences is crucial for finding possible illness markers and stratifying patients with similar symptoms. “ We’ve seen large datasets that estimated a norm across a population and then placed individuals across a range of biomarkers in reference to this population, ” Thomas explains. “ This eventually allows us to find possible markers of illness and stratify differences between patients that supposedly have the same illness. In the case of schizophrenia or other neurological diseases, symptomatic representation doesn’t map well onto the brain on the group level . ” Nicha adds: “ It sounds abstract sometimes talking about finding these different biomarkers to help stratify patients, but that’s important to impact the treatment. In some of my work, we work with children with autism, and no one treatment works for each child. It’s trial and error. If we could somehow, perhaps through baseline imaging, predict that this specific treatment will be effective for this specific child, that kind of personalized or precision medicine approach would be the dream. ” Thomas, Vinod, and Nicha each have personal reasons for focusing on the brain The degree of variability among individuals w same brain disorder, in this case, schizophre Sub