Biomedical Data Science and Machine Learning Applications in Healthcare

Wednesday, October 30, 2019 - 4:30pm to 6:30pm

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Old Chemistry 116


Join the upcoming +DataScience in-person learning experiences. Anyone in the Duke community is welcome to join, there is no fee to attend, and no prior experience is necessary.  Join MEDx Investigator Jessilyn Dunn for her talk on "Biomedical Data Science and Machine Learning Applications in Healthcare."

Despite significant recent advances in molecular genetics and neuroscience, behavioral ratings based on clinical observations are still the gold standard for screening, diagnosing, and assessing outcomes in neurodevelopmental disorders, including autism spectrum disorder, the core of this talk. Such behavioral ratings are subjective, require significant clinician expertise and training, typically do not capture data from the children in their natural environments such as homes or schools, and are not scalable for large population screening, low-income communities, or longitudinal monitoring, all of which are critical for outcome evaluation in multisite studies and for understanding and evaluating symptoms in the general population. The development of computational approaches to standardized objective behavioral assessment is, thus, a significant unmet need in autism spectrum disorder in particular and developmental and neurodegenerative disorders in general.

Here, we discuss how computer vision and machine learning can develop scalable low-cost mobile health methods for automatically and consistently assessing existing biomarkers, from eye tracking (gaze analysis) to movement patterns and affect and facial-based analysis, while also providing tools and big data for novel discovery. We will present results from our multiple clinical studies, where we have already collected the largest available data in the field, as well as the challenges of the discipline. The work presented here is in collaboration with Geri Dawson, Kim Carpenter, Jordan Hashemi, Zhuoqing Cheng, Dmitry Isaev, Matthieu Bovery, Steven Espinosa, Kathleen Campbell, Elena Tenenbaum, and others in this interdisciplinary team of MDs, therapists, engineers, developers, advocates, and most of all, children participants.