By Jessica Johnstone
Friday, December 8, 2023 was a lively day as the Sarah P. Duke Gardens, Kirby Horton Hall was transformed into a hub of quantitative activity, hosting the Health Data Science Poster Showcase. It included 55 posters, each featuring insightful research, showcasing the depth and talent of Duke’s diverse community. From statistics and informatics to machine learning and data engineering, the topics spanned the full spectrum of health data science. Students, fellows, staff, and faculty alike presented their work, illuminating the collaborative spirit that thrives at Duke. The event, championed by Duke AI Health, the Duke Clinical & Translational Science Institute, the Laboratory for Transformative Administration, and the Center for Computational Thinking, was a testament to Duke’s commitment to fostering innovative research.
The event was a resounding success, fostering connections, sparking ideas, and leaving everyone energized by the potential of data-driven health. “The showcase illuminated the depth and impact of health data science across Duke,” Shelley Rusincovitch, MMCi, the event’s director said. “Empowering these collaborations is precisely why we do what we do.”
Michael Pencina, PhD, Chief Data Scientist for Duke Health and Director of Duke AI Health, extended a warm welcome to the audience. He remarked, “This endeavor reflects Duke’s dedication to ethical equitable data science, showcasing the application of advanced natural language processing methods to extract meaningful insights for the future of healthcare.”
Akshay Bareja, PhD, an Assistant Professor in Duke Molecular Physiology Institute, presented the Best Computational Thinking awards from Duke’s Center for Computational Thinking, to Tanner J. Zachem, a PhD student in the Department of Neurosurgery at the Brain Tool Laboratory under Patrick Codd, and Aditya Parekh, MS, a Duke AI Health Data Science fellow in Rohit Singh’s lab. Dr. Bareja commented, “There were so many excellent posters presented. I was particularly struck by the novelty and sophistication of the winner (TumorID) and runner-up (Sceodesic). The Tumor ID team developed a florescence spectroscopy device that can accurately classify tumor type and shows promise as a tool that can be used during surgery to perform real-time tumor identification and classification. Inspired by how flight paths are computed, the Sceodesic team developed a novel gene-program discovery algorithm. The clear and immediate real-world impact of TumorID gave it the edge and the fact that the presenter, Tanner Zachem, is still a first-year PhD student made the achievement all the more impressive!”
Mr. Zavhem’s poster, “Machine Learning and Laser Induced Fluorescence Spectroscopy for In Vivo Brain Tumor Identification” included co-authors Rory Goodwin MD, PhD, and Patrick J. Codd MD. Mr. Parekh’s poster “Sceodesic: Navigating the Manifold of Single-cell Gene Coexpression to Discover Interpretable Gene Programs” included co-authors Sinan Ozbay, MFin, and Rohit Singh, PhD.