Upcoming Events

The Medical Imaging and Data Resource Center (MIDRC) will be hosting an upcoming seminar on Tuesday, May 21. The talk, "The MIDRC Diversity Calculator: A dynamic tool for measuring and monitoring the representativeness of biomedical datasets," will be held virtually at 3PM ET. Held on the third Tuesday of the month, the MIDRC seminar series is an opportunity for members of the medical community at large to hear directly from the MIDRC Team! This session will feature research presentations from MIDRC investigators on new and noteworthy advances, and includes a live Q&A session for all attendees. The speakers for this session will be Robert Tomek, M.S., and Heather Whitney, Ph.D. These virtual seminars are free and open to everyone. We hope you'll join us throughout the year for these engaging discussions. Seminar registration is required to attend. For more information on the seminar series, visit the MIDRC website.

Dexter Pratt (UCSD) will explore issues in developing AI agents that evaluate the behavior of other agents. Agent-based judges will almost certainly have problems with bias and consistency, but can we create judges that are good enough to be useful? Click here to learn more information.

Please join us on Tuesday, June 18th at 12pm-1pm PST/3pm-4pm EST for the lecture “Regulatory Considerations: Health Equity, AI, and Bias ” by Dr. Michael D. Abramoff, MD, PhD Zoom link: https://washington.zoom.us/j/93878229164 Michael D. Abramoff, MD, PhD, is a fellowship-trained retina specialist, computer scientist and entrepreneur. Dr. Michael Abramoff, MD, PhD, (Gold Fellow, ARVO and Fellow, IEEE) is the Robert C. Watzke, Professor of Ophthalmology and Visual Sciences at the University of Iowa, with a joint appointment in the College of Engineering. Dr. Abramoff is also Founder and Executive Chairman of Digital Diagnostics, the Autonomous AI diagnostics company that was the first in any field of medicine to get FDA clearance for an autonomous AI, where the AI makes a medical decision without human oversight, and which, in primary care, it can instantaneously diagnose diabetic retinopathy and diabetic macular edema at the point of care. Dr. Abramoff developed an ethical foundation for autonomous AI that was used during the design, validation, of AI and regulatory and reimbursement pathways for autonomous AI. The results of randomized controlled trials show that it increases clinician productivity, lowers cost, and improves health equity, patient outcomes, and care access. Finally, he is founder of the Healthcare AI coalition, representing many healthcare AI companies, and a founding member and treasurer of FDA’s Collaborative Community on Ophthalmic Imaging. As the author of over 400 peer-reviewed publications in this field, he has been cited over 47,000 times (h-index 80), and is the inventor on 25 issued patents and many patent applications. Dr. Abramoff has mentored dozens of engineering graduate students, ophthalmology residents, and retina fellows. His passion is to use autonomous AI to improve the productivity and accessibility of healthcare. Link to previous lecture recordings and terms of the month: https://aireadi.org/blog

The Medical Imaging and Data Resource Center (MIDRC) will be hosting an upcoming seminar on Tuesday, June 18. The talk, "Introducing MIDRC Helper AI: A Demonstration of Enhanced Medical Imaging Analysis," will be held virtually at 3PM ET. Held on the third Tuesday of the month, the MIDRC seminar series is an opportunity for members of the medical community at large to hear directly from the MIDRC Team! This session will feature research presentations from MIDRC investigators on new and noteworthy advances, and includes a live Q&A session for all attendees. The speakers for this session will be Maryam Vazirabad, M.S., from RSNA; George Shih, M.D., from Weill Cornell Medical College; and Adam Flanders, M.D., from Thomas Jefferson University. These virtual seminars are free and open to everyone. We hope you'll join us throughout the year for these engaging discussions. Seminar registration is required to attend. For more information on the seminar series, visit the MIDRC website.

Please join us on Tuesday, July 16th at 12pm-1pm PST/3pm-4pm EST for the lecture “Policy and Ethics in Innovation: Developing and Applying Ethics and Equity Principles, Terms, and Engagement Tools in AI and Machine Learning”, by Rachele Hendricks-Sturrup, D.H.Sc., M.Sc., M.A. Additional details in the attached documents and message below. Zoom link: https://uchealth.zoom.us/j/81753058557 Bio: Rachele Hendricks-Sturrup, D.H.Sc., M.Sc., M.A., is the Research Director of Real-World Evidence (RWE) at the Duke-Margolis Institute for Health Policy and former Chief Data Governance Officer at the National Alliance Against Disparities in Patient Health. She recently joined the AcademyHealth Advancing Research on Trust initiative as a Scholar in Residence. Dr. Hendricks-Sturrup holds research and practice expertise as a health scientist, engagement expert, and bioethicist. Her work focuses on examining and addressing ethical, legal, social, and implementation issues at the forefront of policy and health innovation. Links to previous lecture recordings and terms of the month: https://vimeo.com/showcase/11167277 https://bridge2ai.org/blog/

Please join us on Friday, July 19 at 1:00 PM PST / 3:00 PM CST / 4:00 PM EST for a lecture on the Bridge2AI Voice dataset, including voice data collection, storage, access, and analysis, presented by Satrajit Ghosh, PhD, Alistair Johnson, DPhil, and Alexandros Sigaras, MS. Satrajit Ghosh is a Principal Research Scientist at the McGovern Institute for Brain Research at MIT, Assistant Professor in the Department of Otolaryngology at Harvard Medical School, and lead of the Standards team in the Bridge2AI Consortium. Dr. Johnson is an Independent Consultant for Glowyr, where he provides support for research and development projects specializing in biomedical data and machine learning. Alex Sigaras is an Assistant Professor of Research in Physiology and Biophysics at Weill Cornell Medicine and lead of the Tools Development and Optimization in the Bridge2AI Consortium. This lecture is the eighth and final webinar in a series from voice AI-experts geared towards the future AI/ML workforce to prepare them work with voice AI. These webinars are hosted by the Skills and Workforce Development (SWFD) team of the Bridge2AI Voice Consortium. The Voice consortium aims to integrate the use of voice as biomarker of health in clinical care to assist in screening, diagnosis, and treatment of a broad range of diseases. The SWFD team is comprised of members from both Oregon Health & Science University (PIs Bill Hersh and David Dorr) and Washington University (PI Philip Payne). Join the meeting here.

Please join us on Tuesday, September 17th at 12pm-1pm PST/3pm-4pm EST for the discussion forum  “Trustworthy Machine Learning”, by Dr. Kush R. Varshney. Zoom link: https://uchealth.zoom.us/j/81753058557 Registration required, register here!  Zoom link: https://uchealth.zoom.us/j/81753058557 Bio: Kush R. Varshney was born in Syracuse, New York in 1982. He received the B.S. degree (magna cum laude) in electrical and computer engineering with honors from Cornell University, Ithaca, New York, in 2004. He received the S.M. degree in 2006 and the Ph.D. degree in 2010, both in electrical engineering and computer science from the Massachusetts Institute of Technology (MIT), Cambridge. While at MIT, he was a National Science Foundation Graduate Research Fellow. Dr. Varshney is an IBM Fellow based at the Thomas J. Watson Research Center, Yorktown Heights, NY, where he directs the Human-Centered Trustworthy Artificial Intelligence team. He was a visiting scientist at IBM Research - Africa, Nairobi, Kenya in 2019. He was the founding co-director of the IBM Science for Social Good initiative from 2015-2023. He applies data science and predictive analytics to human capital management, healthcare, olfaction, computational creativity, public affairs, international development, and algorithmic fairness, which has led to the Extraordinary IBM Research Technical Accomplishment for contributions to workforce innovation and enterprise transformation, and IBM Corporate Technical Awards for Trustworthy AI and for AI-Powered Employee Journey. He and his team created several well-known open-source toolkits, including AI Fairness 360, AI Explainability 360, Uncertainty Quantification 360, and AI FactSheets 360. AI Fairness 360 has been recognized by the Harvard Kennedy School's Belfer Center as a tech spotlight runner-up and by the Falling Walls Science Symposium as a winning science and innovation management breakthrough. He conducts academic research on the theory and methods of trustworthy machine learning. His work has been recognized through paper awards at the Fusion 2009, SOLI 2013, KDD 2014, and SDM 2015 conferences and the 2019 Computing Community Consortium / Schmidt Futures Computer Science for Social Good White Paper Competition. He independently-published a book entitled 'Trustworthy Machine Learning' in 2022, available athttp://www.trustworthymachinelearning.com. He is a fellow of the IEEE. Links to previous recordings and terms of the month: https://vimeo.com/showcase/11167277 https://bridge2ai.org/blog/