10 DAILY CVPR Sunday Congrats, Doctor Joshua! Demand for precision medicine has increased as access to data and computational power has become dramatically more widely available. The influx of information and methodological improvements has ignited the desire for practical precision medicine models that can be used in the clinic to improve patient quality of life. Currently, estimates of personalized treatment effect are based on low-dimensional features, i.e., age. Building the next stage of precision medicine requires using a patient's unique highdimensional information, such as magnetic resonance imaging sequences, X-ray images, ultrasound images, or genetic data. The PVG has been researching the use of multi-modal MRI to improve treatment assignment for patients with multiple sclerosis (MS). MS affects millions of people worldwide and is characterized by the appearance of lesions in the brain and spinal cord. The size, quantity, and number of these Joshua Durso-Finley defended his PhD Thesis in March. He worked as part of the Probabilistic Vision Group (PVG) at McGill University in Montreal. There, he developed methods for estimating treatment response and finding subgroups of responders for patients with multiple sclerosis using multimodal MRI. Under the supervision of Tal Arbel (McGill university and Mila) and with clinical collaborator D.L. Arnold, he developed and validated a treatment effect model that was able to find subgroups of responders to treatment, even in treatments that did not have a significant effect at the group level when all patients are considered. After completing his PhD, Joshua has begun working as a machine learning engineer at Google.
RkJQdWJsaXNoZXIy NTc3NzU=