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Medical Dialogue Virtual Roundtable

Event Details


Join CMU professors Carolyn Rose, Zachary Chase Lipton, and Eric Nyberg, along with government and industry professionals Danica Marinac-Dabic and Sandeep Konam for a panel discussion covering current research trends in the understanding and analysis of medical conversations. Topics will include: extracting information from medical conversations and creating usable summaries of medical-provider/patient conversations.

Recent work on dialogue modeling, medical entity extraction, event and ordering extraction will be discussed, as well as the completion of knowledge graphs. CMU scientists are working with the National Institute of Health, healthcare companies, and large technology providers to better understand key challenges relating to this work.

Wednesday, February 24
2-4:00 p.m. ET
Virtual Program

All participants must register for this event. A Zoom login link will be provided before the virtual program in a confirmation email.


Register by Monday, February 22

Questions? Contact SCS Partnerships



Eric Nyberg

Professor, Language Technologies Institute, School of Computer Science, Carnegie Mellon University

Eric Nyberg is a Professor in the Language Technologies Institute in the School of Computer Science at Carnegie Mellon University. He is Director for the Master's Program in Computational Data Science (formerly known as the M.S. Program in Very Large Information Systems). Nyberg has made significant research contributions to the fields of automatic text translation, information retrieval, and automatic question answering. He received his Ph.D. from Carnegie Mellon University (1992), and his BA from Boston University (1983). He has pioneered the Open Advancement of Question Answering, an architecture and methodology for accelerating collaborative research in automatic question answering. In 2012, Nyberg received the Allen Newell Award for Research Excellence for his scientific contributions to the field of question answering and his work on the Watson project. He received the BU Computer Science Distinguished Alumna/Alumnus Award on September 27, 2013.



Carolyn Penstein Rosé

Professor, Language Technologies Institute, School of Computer Science, Carnegie Mellon University

Carolyn Penstein Rosé is a Professor of Language Technologies and Human-Computer Interaction in the School of Computer Science at Carnegie Mellon University and a research consultant for the National Institute of Health, in the Epidemiology and Biostatistics section of the Rehabilitation Medicine department.  Her research program focuses on computational modeling of discourse to enable scientific understanding the social and pragmatic nature of conversational interactions of all forms, as well as clinical information extraction from medical records and social media.  Her research group’s highly interdisciplinary work, published in over 260 peer reviewed publications, is represented in the top venues of 5 fields: namely, Language Technologies, Learning Sciences, Cognitive Science, Educational Technology, and Human-Computer Interaction, with awards in 3 of these fields.  She is a Past President and Inaugural Fellow of the International Society of the Learning Sciences, Senior member of IEEE, Founding Chair of the International Alliance to Advance Learning in the Digital Era, and Co-Editor-in-Chief of the International Journal of Computer-Supported Collaborative Learning.  She also serves as a 2020-2021 AAAS Fellow under the Leshner Institute for Public Engagement with Science, with a focus on public engagement with Artificial Intelligence.


Zachary Chase Lipton

Assistant Professor of Operations Research and Machine Learning, Tepper School of Business and School of Computer Science, Carnegie Mellon University

Zachary Chase Lipton is an assistant professor at Carnegie Mellon University appointed in both the Machine Learning Department and Tepper School of Business. His research spans core machine learning methods and their social impact and addresses diverse application areas, including clinical medicine and natural language processing. Current research focuses include robustness under distribution shift, breast cancer screening, the effective and equitable allocation of organs, and the intersection of causal thinking with messy data. He is the founder of the Approximately Correct (approximatelycorrect.com) blog and the creator of Dive Into Deep Learning, an interactive open-source book drafted entirely through Jupyter notebooks. He can be found Twitter (@zacharylipton) or GitHub (@zackchase).


Sandeep Konam

Co-Founder/CTO, Abridge

Sandeep Konam is the co-founder and CTO of Abridge (https://www.abridge.com), which uses machine learning to help people understand and follow through on their doctors' advice. Previously, he built multiple health-tech tools, including a web app to match cancer patients to clinical trials, an augmented reality app to aid low vision patients, and a mobile app to analyze blood-sample images and detect cancer biomarkers. He earned a master's degree in robotics from Carnegie Mellon University, where he worked on multi-robot coordination, the interpretability of deep learning models, and enhancing UAVs' perception capabilities. Sandeep is also the founder of Hitloop (https://www.hitloop.it), a human-in-the-loop platform to improve the reliability of machine learning systems and Konam Foundation (https://konamfoundation.org), a non-profit using technology to achieve the Sustainable Development Goals.



Danica Marinac-Dabic

Associate Director, Office of Clinical Evidence and Analysis Center for Devices and Radiological Health, US Food & Drug Administration (FDA)

Danica Marinac-Dabic, MD, serves as the associate director of the Office of Clinical Evidence and Analysis at the Food and Drug Administration (FDA) Center for Devices and Radiological Health (CDRH). Prior to this position, she was the director of the CDRH Division of Epidemiology. Dr. Marinac-Dabic has over 25 years of experience in obstetrics, gynecology, perinatal epidemiology, and regulatory science and surveillance settings. Under her leadership, in 2010 the FDA launched its Medical Device Epidemiology Network (MDEpiNet) to advance the national/international infrastructure (via public private partnership) and innovative methodological approaches to conducting robust studies and surveillance of medical devices. In 2016, Dr. Marinac-Dabic was inducted as a fellow of the International Society for Pharmacoepidemiology and Therapeutic Risk Management (ISPE). Since 2016, Dr. Marinac-Dabic has spearheaded the interoperable Coordinated Registry Networks (CRNs) via ecosystem partnership in 12 clinical areas by linking the national registries data to claims, EHRs and patient-generated data.

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