2019 Summit on AI in Healthcare
March 28-29, 2019 * Omni Orlando Resort at ChampionsGate, Orlando , FL

2019 Summit on AI in Healthcare

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About the Conference

Although there are a myriad of industries and domains that artificial intelligence (AI) could significantly impact and disrupt over the coming years, the healthcare industry is poised to witness the biggest paradigm shift. AI is completely transforming every corner of the healthcare industry and is predicted to save $150 billion annually for the U.S.

This event will focus on healthcare providers, attracting physicians, clinicians and IT leaders from hospitals across the country that are applying AI to solve problems, create opportunities, and leveraging it to deliver new value. They will share their experiences using AI in the clinical care and hospital operations settings. You will come away with a wealth of practical tips and actionable insights that will enable you and your organization to become a leader in AI’s imminent transformation of healthcare. The program is focused on helping you along on your AI journey, at whatever stage you may be. Hear case studies and real world applications of AI in healthcare and its impact on future jobs.

Who Should Attend?

From Hospitals/Health Systems/Health Plans

  • CEO’s/CIO’s/CTO’s
  • Chief Data Officers
  • Business & Technology Executives
  • IT Decision Makers
  • Heads of Innovation
  • IT Operations
  • Data Management
  • Medical Records
  • Director of Artificial Intelligence
  • Product Development
  • Data Architects
  • Scientists and Engineers
  • Telemedicine
  • Virtual Care Executives
  • Business Intelligence
  • Telehealth
  • Innovation Officer
  • Medical Directors

This Event Will Also be if Interest to:

  • Venture Capitalists
  • Investors
  • AI Consultants & Service Providers
  • R&D
  • Solution Providers
  • Robotics

Conference Agenda

Day One – Thursday, March 28, 2019

7:15am – 8:00am
Conference Registration & Networking Breakfast

8:00am – 8:15am
Chairperson’s Opening Remarks

8:15am – 8:55am
Keynote
Common Misconceptions and Future Directions of AI in Medicine

Anthony C. Chang, MD, MBA, MPH, MS
Chief Intelligence and Innovation Officer
Medical Director, The Sharon Disney Lund Medical Intelligence and Innovation Institute (MI3)
Children’s Hospital of Orange Officer

8:55am – 9:35am
The Role of Content in Chatbots and AI in Healthcare
Technology is rapidly transforming the ways we can reach patients and healthcare consumers to deliver impactful content to improve lives, ensure better (patient) compliance, reduce hospitalization, and more. As new engagement channels emerge (such as chatbots, voice, artificial intelligence), organizations will need to invest in developing, structuring and implementing “content” in new ways. Mayo Clinic has been developing and publishing content for decades—join us as we explore how one of the world’s leading academic medical centers is helping to change care continuum and the patient and consumer experiences with health and wellness related content.

Joyce A. Even
Vice Chair of Content Management and Delivery, Global Business Solutions
Mayo Clinic

9:35am – 10:15am
Integrating Artificial Intelligence into Telehealth Platforms
This talk will examine how artificial intelligence can help solve manpower issues as well as reducing mortality and complications in acute hospital-based care. Topics to be discussed will include the following:
-How AI can be used to reduce cost in tele-ICU care
-How machine learning algorithms can be used to reduce complications in the hospital
-How AI can be used to solve manpower issues in multiple subspecialties
-How AI can be used to increase operational efficiency in telehealth

Christian D. Becker, MD, Ph.D.
Associate Medical Director, eHealth Center
Director, Research and Quality
Westchester Medical Center Health Network

10:15am – 10:45am
Networking & Refreshments Break

10:45am – 11:25am
Steps in “Learning” to use Machine Learning in a Payer Organization
Despite machine learning and artificial intelligence has been around for over 50 years, healthcare payer applications of this tool are relatively rare. At WellCare HealthPlans, as part of our Innovations Strategy, we have developed a list of clinical and operational issues that might be solved using this new technology, and are now well into the journey. Today we will present three real world use cases covering financial (identifying COB from member case notes) health quality (identification of diagnosis to improve Medicare Risk Scores) and operational (automatically correcting fax images) and discuss some of the lessons we’ve learned along the way.

Robert Klopotek (tentative)
Vice President IT
WellCare Health Plan, Inc.

Robert London, MD (tentative)
Chief Medical Officer
WellCare of South Carolina, a WellCare Health Plans, Inc. company

11:25am – 12:05pm
Principles for Translating Predictive Models into Clinical Practice
The complexities behind organizational and engineering structures underlying model translations require precise deployment. Through NYU Langone’s Health own work with clinical predictive models, hear principles in regards to people, artificial intelligence, workflow integration, evaluation and infrastructure that underlie their success.

Yin Aphinyanaphongs, MD, PhD
Director of Clinical Predictive Analytics
Assistant Professor, Center for Health Information and Delivery Science
Assistant Professor, Center for Health Information and Delivery Science

12:05pm – 1:05pm
Luncheon

1:05pm – 1:45pm
Data Scientists Are From Mars, Clinicians Are From Venus
Clinicians and data scientists come from very different backgrounds and speak different languages. Bridging that gap is a critical component to being able to successfully execute projects in healthcare. This talk will discuss some of the successful strategies for improving communication to foster collaboration between interdisciplinary teams. Topics will include embedding data scientists in a clinical environment, embedding clinicians in data analysis, and providing clinical education to aspiring data scientists.

David Ledbetter
Senior Data Scientist
>Children’s Hospital of Los Angeles

1:45pm – 2:25pm
Integrating Artificial Intelligence Technologies into Clinical Care
Artificial intelligence in healthcare is helping to fill in the gaps by diligently mining as much data as possible and making helpful suggestions that can lead to potential medical problems being identified earlier. By analyzing a wide variety of data inputs, machine-learning algorithms can detect potential problems before a human could have known about them, helping to make treatment less expensive and more efficient. This session will examine considerations for incorporating AI in healthcare, as well as its impact potential impact on the doctor-patient relationship and patient outcomes. Topics to be discussed will include altering care delivery paradigms, augmenting clinical workflows, and new types of data available that could improve patient care.

James Courtney Fackler, MD
Director, Pediatric Critical Care Medicine
Associate Professor of Anesthesiology and Critical Medicine
Johns Hopkins Medicine

2:25pm – 2:55pm
Networking & Refreshments Break

2:55pm – 3:35pm
Implementation and Quality Science of Integrating AI into Mainstream Clinical Practice
Acceptability and use of innovative technology by healthcare providers at the sharp end of clinical care is challenging even in the face of supporting evidence. This session will highlight and explain the importance of applying implementation and quality science strategies to accelerate adoption of evidence-based AI use in routine healthcare practice and policies. Discussion will include principles and methods for change management, team intelligence, rapid cycle adaptation and collaborative learning. After the session, the audience will have an implementation roadmap to adapt and use in their institutions.

John Chuo, MD, MS
Neonatal Quality Officer
Clinical Lead for Digital Health Evaluation
Children’s Hospital of Philadelphia
Associate Professor of Clinical Pediatrics
Perelman School of Medicine, University of Pennsylvania
Chair, SPROUT (Supporting Pediatric Research in Outcomes and Utilization of Telehealth)

3:35pm – 4:35pm
Panel: Overcoming Artificial Intelligence Barriers in Healthcare
The artificial intelligence boom is poised to revolutionize healthcare, harnessing a wealth of data to offer providers a fuller picture of patients, leading to better and more efficient diagnoses and dramatically improving outcomes. Unleashing AI’s full potential in the healthcare sector will not be a simple task. It will require effort by both AI companies and health care providers to overcome a range of obstacles on the path towards integration of new technologies. Clearing these hurdles will require shifting mindsets and technological refinement, but the payoff for today’s strained healthcare systems will be considerable. This session will examine how to embrace advances enabled by AI, including:
- How AI will equip medical professionals, patients and healthcare systems with the tools needed to augment wellness in the future
- Breaking down organizational silos to accelerate innovation in AI for healthcare
- The impact of culture on AI adoption
- How healthcare providers can address obstacles and help drive AI adoption
- Privacy and security (HIPAA) considerations for AI

Panelists:
Ben Cleveland
Data Scientist
UnityPoint Health

Aalpen Patel, MD
Chair, Geisinger System Radiology
Geisinger Health System

Phyllis Teater
Chief Information Officer
Associate Vice President, Health Services
The Ohio State University Wexner Medical Center

4:35pm – 5:15pm
Leveraging AI in Imaging and Beyond!
In recent years, machine learning (ML) and in particular deep learning has revolutionized the field of computer vision. In addition, we have an unprecedented opportunity to combine data from different sources – EMR, imaging, genomics and apply machine learning for integration. We believe that using large clinical grade, heterogenous data set is extremely valuable in generalizing and translating to clinical tools. Advances in algorithms, vast volume/variety of digital data and compute capabilities have finally reached a point where we can begin to ask questions that we have never asked before. This large volume of data, however, has also led to data overload for the physicians and therefore data waste. Data overload combined with the expected healthcare provider shortage in the next decade means that we need AI - to make sure we can take care of expected increase volume of patients by making the providers more efficient and to help with mundane tasks and easy tasks so that the providers can focus on more complex tasks. The key area we are focusing on are automatic detection/measurement, interpret/integrate findings, and predict outcomes and suggest therapies. The predictive capabilities and therapy suggestion options will enable population management. It is clear that we will need help and what physicians do will change – to what extent and how fast remains to be seen.
Learning Objectives:
- Learn that perfect data does not equate to perfect and generalizable results
- Learn how will (does) AI help physicians be better
- Discover how AI (will) improve patient care
- Learn how AI can help with population management

Aalpen Patel, MD
Chair, Geisinger System Radiology
Geisinger Health System

5:15pm – 6:15pm
Cocktail Reception

Day Two – Friday, March 29, 2019

7:15am – 8:00am
Networking Breakfast

8:00am – 8:15am
Chairperson’s Recap

8:15am – 8:55am
How Chatbots and AI are Changing the Healthcare Industry
Technology is reshaping the healthcare industry. While doctors and researchers push the boundaries of medicine, advances in technology are changing the way patients and doctors communicate and how care is administered. Chatbots and artificial intelligence are two revolutionary technologies that are leading the way in transforming the industry. Thanks to their machine learning-based core, chatbots and AI are naturally evolving day by day. The more qualified chatbots will be getting at understanding symptoms, the less often patients will need to make costly in-person visits to the doctor. This session will examine the benefits these technologies will bring to healthcare, and patients.

Vish Anantraman, MD
Chief Innovation Architect
Northwell Health

8:55am – 9:35am
From Bits to Bedside™: Translating Large-Scale Routine Clinical Datasets into Precision Mammography with Artificial Intelligence
We demonstrate how to use artificial intelligence (AI) approaches to translate big data from routine clinical care into medical innovation. Typically, large healthcare institutions have large-scale quantities of clinical data to facilitate precision medicine through an AI paradigm. However, this so-called ‘big data’ is hardly translated into improved patient care because AI algorithms like deep learning cannot readily ingest or reason over it. We will demonstrate how we use routine clinical data at UCSF to define a multimodal clinical data stack and how we use deep learning and other AI approaches to translate that into precision oncology to better characterize breast cancer and improve patient outcomes.

Dexter Hadley, MD, PhD
Assistant Professor of Pediatrics, Pathology and Laboratory Medicine
Institute for Computational Health Sciences
University of California, San Francisco

9:35am – 10:15am
AI in Medical Imaging: Opportunities and Hurdles
It is becoming increasingly clear that AI is destined to transform the diagnostic imaging industry, both in terms of enhanced productivity, increased diagnostic accuracy, more personalized treatment planning, and ultimately, improved clinical outcomes. AI is vital to tackling the deluge of data challenge in healthcare – and medical imaging is a logical place for AI to prove its worth. The world market for artificial intelligence in medical imaging is forecasted to reach $2 billion by 2023. Topics to be discussed in this session will include:
-Example AI applications in imaging including their promise as well as current limitations
-How medical imaging AI is improving clinical efficiency, hospital operations, and providing life-saving early diagnoses of cancer and other diseases
-How to address communication barriers between clinicians, healthcare executives and IT

Seong Ki Mun, PhD
Professor and Director of the Arlington Innovation Center for Health Research
Virginia Tech

10:45am – 11:25am
How AI Will Take Predictive Analytics to the Next Level
This session will examine the use of predictive analytics in healthcare to better understand where artificial intelligence comes into play. Gain insights to help make informed decisions when thinking about AI adoption. Topics to be discussed will include:
-Types of predictive analytics applications currently in use in healthcare
-Technical and organizational change management challenges
-Communicating with the clinical team to drive change
-Necessary skillsets for translational clinical predictive analytics teams

Collin Stultz
Professor of Electrical Engineering and Computer Science, Institute for Medical Engineering and Science
Massachusetts Institute of Technology

11:25am – 12:05pmm
Artificial Intelligence: Hype, Reality, and Future Applications in Medical Imaging
High profile challenges in machine learning and artificial intelligence such as the Jeopardy! Match in 2011 and Google Deep Mind’s triumph at “Go”, have resulted in unprecedented speculation about the end of radiology. Articles in the New England Journal and JACR by Ezekiel Emanuel in recent months have proclaimed that, “in a few years there may be no specialty called radiology”. Stanford’s Andrew Ng suggested in The Economist that a “radiologist may now be in great danger of being replaced by a machine than his own executive assistant”. This comes after a prominent West Coast start-up proclaimed an end to the “wasted protoplasm, which is the radiologist at the workstation”! Despite these concerns there are numerous reasons why radiologists need not fear AI.
-A wide variety of problems in statistics and specifically in medicine can be solved best with the creation of a “machine” which can provide a simulation or model to discern patterns in a dataset and make predictions.
-Machine learning is an advanced statistical technique that accomplishes this
-Interpretation of medical images is much more difficult than Deep Learning/Machine learning experts have anticipated for a variety of reasons and radiologists will not be replaced for quite a long time
-There are many problems involving quality, efficiency, and safety in medicine and medical imaging that can be addressed with machine learning/deep learning approaches quite effectively. The application of this approach will have a profound impact on the practice of medicine in the future.

Eliot Siegel, MD
Chief of Imaging
VA Maryland Health Care Systems
Professor, Diagnostic Radiology and Nuclear Medicine
Vice Chair of Information Systems
University of Maryland School of Medicine

Workshop – Thursday, March 28, 2019

12:20pm – 2:20pm
Workshop
Human Computation 2.0 (HC2.0)
With the recent advancements in human behavior AI domains and technologies used for body computing, it’s time to reinvent Human Computation. The paradigm has to shift to use Human Computation for disrupting both human sensing & intelligence as well as performance mgmt. & improvisation. HC 1.0 was built upon the intersection of Computation, Body & AI technologies with distributed domains of psychology, behavior sciences, neuroscience, philosophy and more. HC2.0 introduces the third dimension for human morality, performance, instincts and more that completes the ecosystem. This new ecosystem will help us create solutions for broader human wellbeing and outcomes and humanize the future autonomous technologies.
Learning Objectives:
1.How to build intelligence systems that are humanized in understanding motivations, habits and other behavior traits.
2.360 degree measurement of biological health - emotional and engagement combined with physical, bio physical, biometric, cellular, genomic and more.
3.Understanding human vitals and other sensory data in context of biological health computed when used for disease management.
4.Enhancing and enriching human behavior and performance to lead to better health and wellbeing outcomes.
5.Uncovering set of “proxies” humans carry that can fundamentally change the diagnosis/ prognosis as well as treatment management.

Dharmesh Syal
Chief Technology Officer, Partner and Managing Director
BCG Digital Ventures

About the Workshop Leader

Dharmesh is the Chief Technology Officer at BCG Digital Ventures with over 25 years experience leading teams building disruptive and enterprise grade technology platforms for mobile, cloud, distributed systems, advanced intelligence and collaboration.
He is a visionary and a key contributor to seeding of several new digital technologies including human computation, behavior intelligence, emotion AI, IoT orchestrators, cognitive engines, federated cloud, semantic web, SOA open stacks and more.

His recent experience includes leading the build out of:

- Patient Monitoring and Disease Management Platformthat builds on an intelligent continuous patient data platform and applies a balanced overlay of medicine heuristics and deep learning techniques to detect anomalies and initiate care. Launched for oncology, the platform is built to scale across disease types.

-New Gen Blockchain Platform built ground up on TCP/IP stack to scale and support modular consensus, smart contracts and Tx confidentiality. Initial solution Dapps launched for supply chain, payments, asset mgmt. etc. solutions.

Featured Speakers

Anthony C. Chang, MD, MBA, MPH, MS

Anthony C. Chang, MD, MBA, MPH, MS

Chief Intelligence and Innovation Officer,Medical Director, The Sharon Disney Lund Medical Intelligence and Innovation Institute (MI3)

Children’s Hospital of Orange Officer

Joyce A. Even

Joyce A. Even

Vice Chair of Content Management and Delivery, Global Business Solutions

Mayo Clinic

Christian D. Becker, MD, Ph.D.

Christian D. Becker, MD, Ph.D.

Associate Medical Director, eHealth Center,Director, Research and Quality

Westchester Medical Center Health Network

Robert Klopotek

Robert Klopotek

Vice President IT

WellCare Health Plan, Inc.

Robert London, MD

Robert London, MD

Chief Medical Officer

WellCare of South Carolina, a WellCare Health Plans, Inc. Company

Yin Aphinyanaphongs, MD, PhD

Yin Aphinyanaphongs, MD, PhD

Director of Clinical Predictive Analytics,Assistant Professor, Center for Health Information and Delivery Science

NYU Langone Medical Center

David Ledbetter

David Ledbetter

Senior Data Scientist

Children’s Hospital of Los Angeles

James Courtney Fackler, MD

James Courtney Fackler, MD

Director, Pediatric Critical Care Medicine ,Associate Professor of Anesthesiology and Critical Medicine

Johns Hopkins Medicine.

John Chuo, MD, MS

John Chuo, MD, MS

Neonatal Quality Officer,Clinical Lead for Digital Health Evaluation

Children’s Hospital of Philadelphia
Associate Professor of Clinical Pediatrics
Perelman School of Medicine, University of Pennsylvania
Chair, SPROUT (Supporting Pediatric Research in Outcomes and Utilization of Telehealth)

Ben Cleveland

Ben Cleveland

Data Scientist

UnityPoint Health

Aalpen Patel, MD

Aalpen Patel, MD

Chair, Geisinger System Radiology

Chair, Geisinger System Radiology

Phyllis Teater

Phyllis Teater

Chief Information Officer,Associate Vice President, Health Services

The Ohio State University Wexner Medical Center

Vish Anantraman, MD

Vish Anantraman, MD

Chief Innovation Architect

Northwell Health

Dexter Hadley, MD, PhD

Dexter Hadley, MD, PhD

Assistant Professor of Pediatrics, Pathology and Laboratory Medicine,Institute for Computational Health Sciences

University of California, San Francisco

Seong Ki Mun, PhD

Seong Ki Mun, PhD

Professor and Director of the Arlington Innovation Center for Health Research

Virginia Tech

Collin Stultz

Collin Stultz

Professor of Electrical Engineering and Computer Science,Institute for Medical Engineering and Science

Massachusetts Institute of Technology

Eliot Siegel, MD

Eliot Siegel, MD

Chief of Imaging

VA Maryland Health Care Systems
Professor, Diagnostic Radiology and Nuclear Medicine
Vice Chair of Information Systems
University of Maryland School of Medicine

Dharmesh Syal

Dharmesh Syal

Chief Technology Officer, Partner and Managing Director

BCG Digital Ventures

Venue

Omni Orlando Resort at ChampionsGate
1500 Masters Boulevard
Champions Gate, FL 33896
800-843-6664

“Mention BRI Network for the Discounted Rate of $189/night”

Sponsors and Exhibitors

TBA

FAQ

Are there group discounts available?

  • Yes – Register a group of 3 or more at the same time and receive an additional 10% off the registration fee

Are there discounts for Non-Profit/Government Organizations?

  • Yes – please call us at 800-743-8490 for special pricing

What is the cancellation policy?

  • Cancellations received 3 weeks prior to the event will receive a refund minus the administration fee of $185. Cancellation received less than 3 weeks prior to the event will receive a credit to a future event valid for one year.

Can the registration be transferred to a colleague?

  • Yes – please email us in writing at info@brinetwork.com with the colleague’s name and title

Where can I find information on the venue/accommodations?

  • Along with your registration receipt you will receive information on how to make your hotel reservations. You can also visit individual event page for specific hotel information. The conference fee does not include the cost of accommodations.

What is the suggested dress code?

  • Business casual. Meeting rooms can sometimes be cold so we recommend a sweater or light jacket
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