machine learning to be available clinically,” he says. “There are other ways to do this. Some people look at health records at the text data of the patient. Some people look at the genomics data of the patient to build these models. I haven’t seen a lot of deep predictive models using this kind of data unique to the individual. I hope this is a guideline for people.” Joshua’s regular work revolves around building and refining these kinds of models. He is currently working with colleagues at MILA to construct time series models and investigate how they can be adapted for causal inference. He speaks highly of his supervisor Tal Arbel. “Tal has a very good vision of what to do,” he smiles. “She has the foresight to know where the field is going. She’s seen it all and knows what’s important, what needs to be done, and how to do it. It’s been excellent working with her.” We asked Tal what is special about this work. “This work is particularly exciting to us because causal models for image-based based personalized medicine represent a new area within medical imaging, with the potential for not only improving individual patient outcomes and but also drug development in clinical trials,” she said. “In this work we show how the integration of uncertainty-aware causal models for personalized medicine sets the stage for safer and more reliable image-based personalized medicine.” After MICCAI, Joshua intends to take an immediate vacation in Vancouver. Despite studying in Canada, he hails from Rhode Island in the US, where he tells us residents possess a unique privilege. “Every Rhode Islander has an automatic license to dig up clams!” he laughs. “I don’t think people know that about Rhode Island. You can go to any lake you want, find clams, and dig them up. It’s very popular!” To learn more about Joshua’s work, visit Poster 4 this afternoon at 13:00-14:30 in the Poster Hall. 11 DAILY MICCAI Tuesday In this Zürich shot: Tal, Joshua, Chelsea Myers-Colet (a graduated master's student from Tal's lab) and Jean-Pierre Falet (graduated masters student at McGill who is a co-author on this paper) Joshua Durso-Finley
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