AI in Practice
February 12, 2020
Hilton New York Midtown
Co-located with AAAI-20
The 2020 edition of AI in Practice will focus on emerging applications of AI in healthcare. We are aiming to offer a venue for exchanging ideas among participants from different disciplines, from general computer science, to AI and ethics, to medicine and public health. The event program will include keynotes, invited talks, and a discussion panel.
Organizers: Evgeniy Gabrilovich (Google Health) and Ashish Jha (Harvard School of Public Health)
- Vivian Lee, President, Health Platforms, Verily Life Sciences
- Aneesh Chopra, President, CareJourney, former first CTO of the United States
- Isaac Kohane, Professor and Chair, Department of Biomedical Informatics, Harvard Medical School
- Honor Hsin, Kaiser Foundation
- Leo Celi, Clinical Research Director, Laboratory of Computational Physiology, Massachusetts Institute of Technology
- John Brownstein, Chief Innovation Officer, Boston Children’s Hospital
- Kira Radinsky, Technion/Diagnostic Robotics
- Prem Ramaswami, Sidewalk Labs
Moderator: Dr. Lisa Simpson (AcademyHealth)
Dr. Abnousi is the Head of Healthcare – Research at Facebook and a practicing Interventional Cardiologist. He also serves as Innovation Advisor to the American College of Cardiology, Professor Adjunct at Stanford University School of Medicine, and Assistant Professor Adjunct at Yale University School of Medicine. He has previously led innovative healthcare efforts at companies such as McKinsey and Google, and has served as Founder and CMO of CorDynamix Inc., an interventional heart failure company. He completed Fellowships in Cardiovascular Medicine and Interventional Cardiology, as well as Residency in Internal Medicine at Stanford University Medical Center. He was previously a resident surgeon at the University of California, San Francisco. He completed his MD at Stanford University School of Medicine, MBA from Oxford University, and MSc in Health Policy, Planning, & Financing from the London School of Economics.
President, CareJourney, Former U.S. Chief Technology Officer (2009-2012)
Talk Title: Connecting Dots: How Open Data, Open APIs, and Payment Reform will Fuel Care Delivery Reform
Abstract: The need to reform the way we delivery care continues as fiscal, access and quality pressures continue to mount. Building on the progress of the Obama Administration, the Trump Administration has launched the “MyHealthEData” initiative anchored on consumer-directed health exchange; opened up more government data for measuring performance, including Medicare Advantage and Medicaid encounters; and added more risk-based alternative payment models. In this presentation, Chopra shares his views on how AI-powered consumer-trusted applications will help patients make better decisions at each step of their care journey.
Aneesh Chopra is the President of CareJourney, an open data service that democratizes care interventions research for organizations on the move to value. He served as the first U.S. CTO and authored “Innovative State: How New Technologies Can Transform Government.”
Chief Innovation Officer, Boston Children’s Hospital
Talk Title: Optimizing the Patient Journey with AI
Abstract: Through social media, forums and online communities, wearable technologies and mobile devices, there is a growing body of health-related data that can shape our assessment of human illness. Collectively, this data comprises an individual’s ‘digital phenotype’ – unique, unsolicited and real-time information about a person’s health. Our current research focuses on using digital phenotypes for population health surveillance, specifically to identify and analyze specific sub-populations over space and time with the goal of better understanding patient behavior and disease dynamics. Some current research topics include foodborne illness, insomnia, autism, febrile illness, and patient experience.
John Brownstein, PhD is Professor of Biomedical Informatics at Harvard Medical School and is the Chief Innovation Officer of Boston Children’s Hospital. He directs the Computational Epidemiology Lab and the Innovation and Digital Health Accelerator both at Boston Children’s. He was trained as an epidemiologist at Yale University. Dr. Brownstein is also Uber’s healthcare advisor and co-founder of digital health companies Epidemico and Circulation.
Leo Anthony Celi
Massachusetts Institute of Technology, Harvard Medical School
Talk Title: An Awakening in Medicine: The Partnership of Humanity and Intelligent Machines
Abstract: As many papers regarding the applicability and challenges regarding AI in medicine have been published, there has been little mention of the need and transformative potential of data infrastructure. It is well established that AI requires data. However, the infrastructure to aggregate this data at scale, to train and retrain models is considerable and has historically been beyond the capabilities of individual healthcare organizations or broader health systems. Without investment in health data infrastructure, opportunities for AI in healthcare will remain just that – opportunities.
As clinical research director and principal research scientist at the MIT Laboratory for Computational Physiology, and as a practicing intensive care unit physician at the Beth Israel Deaconess Medical Center, Leo brings together clinicians and data scientists to support research using data routinely collected in the process of care. His group built and maintains the publicly-available Medical Information Mart for Intensive Care (MIMIC) database and the Philips-MIT eICU Collaborative Research Database, with more than 12,000 users from around the world. Leo is the course directors for HST.936 – global health informatics, and HST.953 – collaborative data science in medicine, both at MIT. (LinkedIn)
Greg Corrado, PhD
Greg Corrado is a Google Distinguished Scientist and the Senior Director of the Research & Innovations division of Google Health. As a co-founder of the Google Brain Team, he helped spearhead Google’s expansive use of deep learning across dozens of products and services. Now having focused on healthcare as the single greatest opportunity to apply AI for the public good, he oversees research in genomics, clinical predictions, medical image interpretation, and novel sensors. In his career as an individual scientist, he worked for decades at the nexus of artificial intelligence and computational neuroscience, and has published in fields ranging from behavioral economics, to particle physics, to natural language understanding. Before coming to Google, he worked at IBM Research on neuromorphic silicon devices and large-scale neural simulations. He did his graduate studies in both Neuroscience and in Computer Science at Stanford University, and his undergraduate work in Physics at Princeton University.
Honor Hsin, MD PhD
Talk Title: AI in Mental Health Care: Challenges and Opportunities
Abstract: Mental illnesses affect 1 in 4 individuals across the globe today, and clinical depression is now the leading cause of disability worldwide. Large gaps exist in both our understanding of mental health disorders and our ability to generate clinical insights from real world practice. Here we will discuss the challenges and potential opportunities that AI could provide in the clinical practice of mental health care. Honor Hsin is a clinical psychiatrist at Kaiser Permanente in the departments of Adult Psychiatry and Addiction Medicine, where she is also engaged in quality improvement research. She was previously a clinician scientist at Verily Life Sciences, where she helped launch the mental health division under the direction of Tom Insel, former director of the National Institute of Mental Health, and served as principal investigator of the Project Baseline Mood Study, an initiative to develop digital biomarkers of clinical depression. She is passionate about promoting mental and emotional health with digital innovation and health systems improvement.
Harvard Medical School
Talk Title: Following the Money: Expected and Unexpected Payoff for AI in Medicine
Abstract: On one hand, machine learning, especially as applied to medical imaging such as radiology, pathology, dermatology, is going to change the quality and reliability of diagnostic and prognostic performance in those specialties. On other hand, the business model for such physician-extending or physician-replacing service is still under development, and different stakeholders have different versions of that plan. The business model that is very clear–for better or worse–for AI applications in medicine, center around how medicine is paid. We already have a large IT industry whose only job is to push the bill up or down depending on whether you’re the payor or provider. These include the tasks of “upcoding”, denial of payment, referral of patients or refusal of referral, and allowing flexibility in which medications–brand names or generics–are used. These money-laden transactions are well-documented and are constrained by multiple rules, and the pertaining data is plentiful. It therefore is to be expected that the perhaps less glamorous but most highly-trained/tuned machine learning algorithms will be those that address these unglamorous administrative activities underlying our healthcare system. I will also discuss how we can develop decision support tools for medicine that does an end run around the distortions created by the financial structures of institutionalized medicine.
Isaac Kohane, MD, PhD is the inaugural Chair of the Department of Biomedical Informatics and the Marion V. Nelson Professor of Biomedical Informatics at Harvard Medical School. He develops and applies computational techniques to address disease at multiple scales— from whole healthcare systems as “living laboratories” to the functional genomics of neurodevelopment with a focus on autism. Kohane’s i2b2 project is currently deployed internationally to over 120 major academic health centers to drive discovery research in disease and pharmacovigilance (including providing evidence on drugs which ultimately contributed to “boxed warning” by the FDA). (LinkedIn)
CTO and Chairperson, Diagnostic Robotics
Talk Title: Data Science in HealthCare: Cutting the lines in the Emergency Departments
Abstract: Let us imagine a world where the most advanced technologies in the field of artificial intelligence and sensory systems are harnessed to make healthcare better, cheaper, and more widely available. I will share my ongoing efforts on solving a world-wide challenge – strained health budgets and workforces, with a cutting-edge solution – a human-machine hybrid AI diagnostic system that represents the future of medicine.
Specifically, I will present empirical AI solutions for healthcare systems, providing services to patients, providers and insurers, serving more than 40 millions people worldwide. I will present clinical results, challenges and algorithmic solutions.
Dr. Kira Radinsky is the chairman and CTO of Diagnostic Robotics, where the most advanced technologies in the field of artificial intelligence are harnessed to make healthcare better, cheaper, and more widely available. Dr. Radinsky has founded SalesPredict, acquired by eBay in 2016 and served as eBay Chief Scientist (IL). She gained international recognition for her work at the Technion and Microsoft Research for developing predictive algorithms that recognized the early warning signs of globally impactful events, as disease epidemics and political unrests. In 2013, she was named one of MIT Technology Review’s 35 Young Innovators Under 35 and in 2015 Forbes included her as “30 Under 30 Rising Stars in Enterprise Tech”. She is a frequent presenter at global tech and industry conferences, including TEDx, Wired, Strata Data Science, Techcrunch and publishes in HBR. Radinsky also serves as a board member in Israel Security Authorities and technology board of HSBC bank. She also holds a visiting professor position at the Technion focusing on the application of predictive data mining in medicine.
Head of Product, Sidewalk Labs, Inc.
Talk Title: The City of the Future
- First, it helps planners generate not just one or two but billions of comprehensive planning scenarios (using machine learning and computational design). As well as visualizing complex high-dimensional decision spaces.
- Second, it evaluates a wide array of impacts these different scenarios could have on key quality-of-life measures, producing a set of options that best reflects holistic priorities and understanding how these options are interrelated.
Prem Ramaswami is Head of Product at Sidewalk Labs where he uses technology to radically improve the quality of urban life. He leads a team of Product Managers and Designers at the intersection of urban policy and technology to build the city of the future. Previously, Prem led Google Search’s Social Impact projects in the domains of Health, Civics, Education, Arts & Culture, Crisis Response, and Social Good. Prem graduated from Carnegie Mellon with a degree in Computer & Biomedical Engineering (‘04), has an MBA from Harvard Business School (‘13), and completed an executive medical training at Harvard Medical School in 2017.
Dr. Lisa Simpson
James N. Weinstein
Evgeniy Gabrilovich and Ashish Jha, AI in Practice Cochairs
|10:05-10:50||Plenary Talk: Vivian Lee (Verily Life Sciences)|
|10:50-11:15||Zak Kohane (CareJourney)|
Panelists: Freddy Abnousi (Google), Greg Corrado (Facebook),
Jim Weintstein (Microsoft)
Moderator: Lisa Simpson
|14:00-14:25||Invited talk: Honor Hsin (Kaiser Foundation)|
|14:25-14:50||Invited talk: Leo Celi (Massachusetts Institute of Technology)|
|14:50-15:15||Invited talk: John Brownstein (Boston Children’s Hospital)|
|15:45-16:10||Invited talk: Kira Radinsky (Diagnostic Robotics)|
|16:10-16:35||Invited talk: Prem Ramaswami (Sidewalk Labs)|
|16:45-17:30||Plenary Talk: Aneesh Chopra|
|17:45-18:45||Networking / Discussion|