AI in Practice Program

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AI in Practice Panel: From Keyboard to Bedside: Connecting AI Solutions to Health Care Problems

February 24, 10:30 – 11:30 AM PST

Moderator: Martin Michalowski, Assistant Professor, University of Minnesota School of Nursing
Panelists: David Buckeridge, Professor, McGill University; Chief Digital Health Officer, McGill University Health Centre; Associate Member, Mila; Maxim Topaz, Elizabeth Standish Gill Associate Professor of Nursing, Columbia University Medical Center; Peter Liu, Chief Scientific Officer and VP of Research, University of Ottawa Heart Institute, Professor of Medicine and Physiology, University of Toronto and University of Ottawa

AI solutions directed towards health care are often developed without a real health-related problem to solve. What is being done and what is still needed to bridge the gap between AI developers’ expertise and health care providers’ needs?

Martin Michalowski

Assistant Professor, University of Minnesota School of Nursing

Dr. Michalowski is an Assistant Professor in the School of Nursing and a member of the Nursing Informatics Faculty at the University of Minnesota. He is a Senior Researcher in the Mobile Emergency Triage (MET) Research Group at the University of Ottawa and serves as Director of Machine Learning Research at Treatment.com. His research portfolio includes novel contributions in the areas of information integration, record linkage, heuristic-based planning, constraint satisfaction problems, and leveraging artificial intelligence (AI) methods in nursing informatics research. His interdisciplinary research brings advanced AI methods and models to clinical decision support at the point of care and to personalized medicine. He strives to improve patient outcomes through the development and adoption of AI-based technology in health care.

Dr. Michalowski earned his Ph.D. in Computer Science from the University of Southern California, where he solved automated reasoning problems. In 2018 he was elected Senior Member of the Association for the Advancement of Artificial Intelligence (AAAI) and in 2021 he was named to the Fellows of the American Medical Informatics Association (FAMIA). He authored and co-authored over 65 peer-reviewed articles on a range of AI-related topics and served on the program committees for various informatics and computer science conferences including AAAI, AMIA, IJCAI, ACMGIS, ICAPS, and ISWC. Dr. Michalowski is the organizing chair of the International Workshop on Health Intelligence (W3PHIAI) that is held at the AAAI annual conference. He was co-chair of the 2020 International Conference on Artificial Intelligence in Medicine (AIME 2020) and serves in the same role for AIME 2022. His research has received funding from the NSF, NIH, DARPA, DoD, and various private foundations. His work has resulted in two patents and several startup companies.

David Buckeridge

Professor, McGill University; Chief Digital Health Officer, McGill University Health Centre; Associate Member, Mila

David Buckeridge is a Professor in the School of Population and Global Health and the Chief Digital Health Officer at the McGill University Health Center. Holding a Canada Research Chair (Tier 1) in Health Informatics and Data Science, he projects health system demand for the Canadian province of Quebec, leads Data Management and Analytics for the Canadian Immunity Task Force, and supports the World Health Organization in monitoring global immunity to SARS-CoV-2. He has a MD (Queen’s), a MSc in Epidemiology (Toronto), a PhD in Biomedical informatics (Stanford), and is a Fellow of the Royal College of Physicians of Canada.

Maxim Topaz

Elizabeth Standish Gill Associate Professor of Nursing at the Columbia University Medical Center

Maxim Topaz, PhD, RN, MA, is the Elizabeth Standish Gill Associate Professor of Nursing at the Columbia University Medical Center. He is also affiliated with Columbia University Data Science Institute and the Center for Home Care Policy & Research at the Visiting Nurse Service of New York. His research focusses on data science and he finds innovative ways to use the most recent technological breakthroughs, like text or data mining, to improve human health. Dr. Topaz’s research moto is “Data for good”. Dr. Topaz is one of the pioneers in applying natural language processing on data generated by nurses. His current work focusses on developing natural language processing solutions to advance clinical decision making. In the past, Dr. Topaz was involved with health policy (national and international levels), leadership (e.g. Chair of the Emerging Professionals Working Group of the International Medical Informatics Association) and health entrepreneurship. Dr. Topaz’s clinical experience is in internal and urgent medicine. He earned his PhD degree as a Fulbright Fellow at the University of Pennsylvania and his Masters and Bachelors degrees from the University of Haifa, Israel. He completed a postdoctoral fellowship at the Harvard Medical School and Brigham Women’s Hospital. He served as a Senior Lecturer at the School of Nursing, University of Haifa (Israel) where he was heading a Health Information Technology Lab. He published more than ninety articles on topics related to health informatics and received numerous prestigious awards for his work.

Peter Liu

Chief Scientific Officer and VP of Research of the University of Ottawa Heart Institute, and also Professor of Medicine and Physiology at the University of Toronto and Ottawa

Dr. Peter Liu is currently the Chief Scientific Officer and VP of Research of the University of Ottawa Heart Institute, and also Professor of Medicine and Physiology at the University of Toronto and Ottawa. He is the former Scientific Director of the Institute of Circulatory and Respiratory Health at the Canadian Institutes of Health Research, the President of International Society of Cardiomyopathy & Heart Failure of World Heart Federation, and inaugural Director of the Heart & Stroke/Lewar Centre at University of Toronto. He received his MD degree from University of Toronto, and postgraduate training at Harvard University. His laboratory investigates the causes and treatments of heart failure, role of inflammation and identification of novel biomarkers and targets for intervention in cardiovascular diseases. He has published over 400 peer reviewed articles in high impact journals, and received numerous awards in recognition of his research and scientific accomplishments. He has chaired scientific sessions of the Heart Failure Society of America, International Society of Heart Research and Human Proteomic Organization, amongst others. He is also champion for knowledge translation, integrating the cardiovascular prevention guidelines and healthy heart policy in Canada and internationally, including the C-CHANGE guidelines.

AI in Practice Panel: The Commercialization of AI in Health

February 25th 10:30am – 11:30am PST

Moderator: Matthew Michelson, President, Genesis AI (Genesis Research); Co-Founder & CEO (Evid Science)
Panelists: Jeffrey De Flavio, Partner and Entrepreneur-in-Residence at AlleyCorp, Co-Founder & Executive Chairman (Diana Health, Affect Therapeutics, and Pearl Health); Jeff Chang, Co-Founder & CPO (Rad AI); Yinhan Liu, Co-founder & CTO (Birch.AI)

The commercialization of AI applications in health is accelerating at an incredible pace. What is needed to make AI methods applied to health care deployable and profitable?

Matthew Michelson

President, Genesis AI (Genesis Research); Co-Founder & CEO (Evid Science)

Matthew Michelson is technology executive focused on building “deep tech” companies, especially within the Artificial Intelligence space. He currently serves as the President of Genesis AI, at Genesis Research, the group developing next generation NLP technologies for the Life Sciences industry (acquired by GHO Partners in 2021). Prior, he was the co-founder and CEO of Evid Science, a venture-backed start-up using NLP to automatically extract results from the medical literature (acquired by Genesis Research in 2020). His interests vary from technical duties to scientific publishing to fundraising from both government and venture capital sources.

Jeffrey De Flavio

Partner and Entrepreneur-in-Residence at AlleyCorp; Co-Founder & Executive Chairman (Diana Health, Affect Therapeutics, and Pearl Health)

Jeffrey De Flavio is a physician and entrepreneur working to improve the health of underserved people. His first venture-backed medical practice (Groups Recover Together) takes an innovative approach to helping rural opiate users and currently has over 100 in-person offices across the country, along with a digital platform for those in even more far flung areas. As Groups’ Founder, Dr De Flavio led the company to become the leading national provider of value-based addiction treatment. In 2017 he co-Founded Tempest, a digital recovery platform for people who want to change their relationship with alcohol. Jeffrey is currently a Partner and Entrepreneur in Residence with AlleyCorp and serves as co-Founder and Executive Chairman of Diana Health, a hospital services company reinventing maternity care; Affect Therapeutics, which has developed the first digital therapeutic for Stimulant Use Disorder; and Pearl Health, which enables primary care physicians to provide value-based treatment to Medicare beneficiaries. Dr. De Flavio is currently developing new projects focused on enabling social service providers to access insurance reimbursement (Nightingale; using EEG derived digital biomarkers to better treat neuropsychiatric disease (Synapse Bio); and developing a value-based digital MSO for cardiology. He is recruiting Venture Fellows to work with him at AlleyCorp and always interested in meeting with scientists, researchers or other technical specialists with a passion for improving health outcomes.

Jeff Chang

Co-Founder & CPO (Rad AI)

Dr. Jeff Chang is an ER radiologist and co-founder of Rad AI. After starting medical school at NYU at age 16, Jeff became the second youngest US physician on record. He did graduate work in machine learning at the University of Edinburgh, fellowship in musculoskeletal MRI, and has an MBA from UCLA Anderson. He has also been a practicing radiologist with Greensboro Radiology for the past decade, launching their Emergency Radiology section in 2010.

Rad AI is building an AI-driven platform to streamline radiology workflow, ranging from customized report impression automation, to automatically tracking and closing the loop for follow-up of incidental findings, saving radiologists time and effort while helping to improve patient care. Rad AI is funded by Artis Ventures, as well as OCV Partners, Kickstart Fund, and Gradient Ventures, Google’s AI fund. Prior to Rad AI, Jeff co-founded Doblet, a Y Combinator hardware startup, coordinating engineering, prototyping and manufacturing efforts. Jeff has prior experience in venture capital and private equity, and is an angel investor in a number of AI and other deep tech startups.

Yinhan Liu

Co-founder & CTO (Birch.AI)

Yinhan co-founded Birch.AI in 2020, where she aims to automate complex healthcare related processes by AI. Prior Birch.AI She worked at Facebook AI Research on NLP, where she published some highly influential papers including Roberta and Bart. She is a big fan of crabbing in the Pacific Ocean.

AI in Practice Panel: Applications and Implications of Deep AI for Personalizing Health Interventions

February 26, 10:30 AM – 11:30 AM PST

Moderator: Eran Halperin, SVP of AI and Machine Learning in Optum Labs (United Health Group), and a professor in the departments of Computer Science, Computational Medicine, Anesthesiology, and Human Genetics at UCLA
Panelists: Shamim Nemati, Director, Predictive Health Analytics, UC San Diego Health, Department of Biomedical Informatics; James Zou, Assistant Professor, Stanford University, Faculty Director, Stanford AI4Health; Corey Arnold, Professor,
Deptartments of Radiology, Pathology, Electrical & Computer Engineering, and Bioengineering, UCLA

Deep AI combined with increasingly large and available data has transformed the way health care providers personalize treatments to specific patients. What are the emerging applications of Deep AI for developing personalized interventions and what implications do they have on the provision of care?

Eran Halperin

SVP of AI and Machine Learning in OptumLabs (United HealthGroup)

Eran Halperin is the SVP of AI and Machine Learning in OptumLabs (United HealthGroup), and a professor in the departments of Computer Science, Computational Medicine, Anesthesiology, and Human Genetics at UCLA. Prior to his current position, he held research and postdoctoral positions at the University of California, Berkeley, the International Computer Science Institute in Berkeley, Princeton University, and Tel-Aviv University. Dr. Halperin’s lab developed methods for a variety of health-related domains, including different genomic domains (genetics, methylation, microbiome, single-cell RNA), and medical applications (medical imaging, physiological waveforms, and electronic medical records). He published more than 150 peer-reviewed publications, and he received various honors for academic achievements, including the Rothschild Fellowship, the Technion-Juludan prize for technological contribution to medicine, the Krill prize, and he was elected as an International Society of Computational Biology (ISCB) fellow.

Shamim Nemati

Director, Predictive Health Analytics, UC San Diego Health, Department of Biomedical Informatics

Dr. Nemati obtained his Ph.D. degree in Electrical Engineering and Computer Science from MIT in 2013, followed by two years of postdoctoral fellowship at the Harvard Intelligent Probabilistic Systems group focused on the application of deep learning and reinforcement learning techniques to healthcare data. Dr. Nemati is currently the Director of Predictive Health Analytics at the UC San Diego (UCSD) Health and an Assistant Professor of Biomedical Informatics at UCSD where he leads an NIH-funded critical care informatics research group. He has published in several areas of research, including advanced signal processing and machine learning techniques, computational neuroscience/brain-machine interface, and predictive monitoring in intensive care, resulting in over 80 peer-reviewed publications.

James ZouJames Zou

Assistant Professor, Stanford University, Faculty Director, Stanford AI4Health

James Zou is an assistant professor of biomedical data science and, by courtesy, of CS and EE at Stanford University. He is also the faculty director for Stanford AI4Health. James’ group develops and deploys novel machine learning algorithms to tackle biomedical and healthcare challenges. He also works on improving the broader impact of AI by making models more reliable, transparent and fair. He has received a Sloan Fellowship, NSF CAREER Award, Chan-Zuckerberg Investigator award, faculty awards from Google, Tencent and Amazon, and several paper awards at top CS venues including the 2019 RECOMB Best Paper.

Corey Arnold

University College London

Corey Arnold is a professor of radiology and pathology at UCLA, with courtesy appointments in bioengineering and electrical & computer engineering. He leads the Computational Diagnostics lab, which performs translational research and development in machine learning for medical image analysis, computational phenotyping, natural language processing, and multi-modal disease modeling.