BIDS-BCHSI Research Xchange Forum — Medical Imaging in Oncology
Date: Tuesday, June 1, 2021
Time: 12:30-1:30 PM Pacific Time
Location: Virtual Participation
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12:30-12:50 PM — Scaling the Impact of PSMA-PET in Clinical Decision Making
Elizabeth Smith, 2020-2022 I4H Fellow
Abstract: Prostate cancer is the most common cancer and third-leading cause of cancer death for men in the United States. In December 2020, the FDA granted approval to UCSF and UCLA for the use of 68Ga-PSMA-11, a positron emission tomography (PET) radiotracer that specifically labels prostate cancer cells, based on clinical trials that demonstrated improved sensitivity for detecting cancerous lesions compared with the current standard of care. Elizabeth will present progress towards building an Artificial Intelligence-based tool to standardize interpretation and minimize interobserver variability of 68Ga-PSMA-11 PET reconstructions.
12:50-01:10 PM — A Treatment Recommendation System for CNS Lymphoma
Reza Eghbali, 2020-2022 I4H Fellow
Abstract: CNS lymphoma is a non-systematic variant of lymphoma that involves the central nervous system. There are multiple treatment options for CNS lymphoma and substantial variation of treatment choice in clinical practice. Our goal is to develop a system for assessing each treatment based on imaging and clinical biomarkers that can assist physicians in choosing the best treatment for the patient with an eye towards the development of tools that can be useful for other neurological conditions. These tools include a system for longitudinal MRI analysis of brain tumors which is also of value for many other conditions such as low-grade glioma, glioblastoma, etc. In this talk, we present our preliminary results based on the analysis of the data extracted from the medical records and MR imaging of CNS lymphoma patients.
01:10-01:30 PM — Q&A
The BIDS-BCHSI Research Xchange Forum is an open discussion platform for the interdisciplinary exchange of ideas and research projects at the intersection of healthcare and data science. Participants are invited to engage in a variety of activities, including presentations of work-in-progress, discussions and critiques of recent papers and AI methods in healthcare, introductions to new tools and methods, and opportunities to foster new collaborations. Invited speakers include leading voices in AI and Healthcare, and active conversations invite participants to share fresh perspectives. Clinicians and physicians with an interest in data science methods and tools, as well as data science faculty and researchers with applications or interests in the healthcare and health sciences, are welcome and encouraged to participate. Regular participants will also include the I4H Fellows, as well as post-docs, staff, and faculty from UC Berkeley, UCSF, and Johnson & Johnson. The immediate goals of this Forum are to share our current research projects with a wider audience, and to increase engagement and improve communication among the three host organizations. Meetings are now held virtually on the first Tuesday of each month at 12:30-1:30 PM Pacific Time, and interested members of the UC Berkeley, UCSF, and Johnson & Johnson communities are invited to sign up for this group's mailing list to receive information about upcoming webinars. Please contact InnovateForHealth@berkeley.edu for more information.
Speaker(s)
Elizabeth Smith
Dr. Elizabeth Smith is a biophysicist and data scientist who is passionate about using data and algorithms to improve lives and make work more efficient. She spent the past five years at a geospatial analytics startup where she applied artificial intelligence / machine learning to build software products from terabytes of satellite imagery. Her postdoctoral fellowship at UCSF and the Advanced Light Source focused on developing novel methods to image, reconstruct, co-align and analyze features within three-dimensional tomographic reconstructions. Dr. Smith has a PhD in biophysics from the University of Wisconsin, Madison, and a bachelors in physics from Pomona College.
Reza Eghbali
Dr. Reza Eghbali received his Ph.D. in Electrical Engineering and a master's degree in Mathematics from the University of Washington, Seattle. He has a B.Sc. in Electrical Engineering from Sharif University of Technology, Tehran. Before joining Innovate For Health, Reza was a member of the machine learning and security team at Cisco Tetration Analytics, where he developed and implemented online learning algorithms for detecting network security threats in real-time. Reza was a Simons Institute Research Fellow at UC Berkeley in the 2017-18 academic year. He visited the institute for the programs on “Bridging Continuous and Discrete Optimization” and “Brain and Computation,” where he worked on modeling the corticothalamic feedback in the early visual system. His research interest lies in the areas of optimization algorithms, machine learning, and computational neuroscience.