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Thursday, August 22 • 9:30am - 10:15am
Advancing Cancer Research with Deep Learning Image Analysis

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Histopathological images are the gold standard tool for cancer diagnosis, whose interpretation requires manual inspection by expert pathologists. This process is time-consuming for the patients and subject to human error. Recent advances in deep learning models, particularly convolutional neural networks, combined with big databases of patient histopathology images will pave the path for cancer researchers to create more accurate guiding tools for pathologists. In this talk, I will review the latest advances of big data in healthcare analytics and focus on deep learning applications in cancer research. Targeted at a general audience, I will provide a high-level overview of technical concepts in deep learning image analysis, and describe a typical cloud-based workflow for tackling such big data problems. I will conclude my talk by sharing some of our most recent results based on a wide range of cancer types. 

avatar for Mohammad Soltanieh-ha, PhD

Mohammad Soltanieh-ha, PhD

Clinical Assistant Professor, Boston University - Questrom
Mohammad is a faculty at Boston University, Questrom School of Business, where he teaches data analytics and big data to master's students. Mohammad's current research area involves deep learning and its applications in cancer research.

Thursday August 22, 2019 9:30am - 10:15am EDT
Room 406 595 Commonwealth Avenue, Boston, MA 02215, USA