ABAIM Review Course

Date

Oct 08 - 09 2021

Time

EST
9:00 am - 5:00 pm

The ABAIM AI in Medicine Review Course is a comprehensive, two-day course on basic concepts in artificial intelligence in clinical medicine and healthcare designed by a team of clinician-data scientists as well as clinicians with an AI focus and data scientists who are involved in healthcare. This course is for all who are interested in having an overall review of concepts and applications in artificial intelligence in clinical medicine and healthcare.

About the course:

  • The format is “flipped” in that much of the review will be faculty discussing (not presenting) slides
  • In addition, the attendees are encouraged to ask questions throughout the sessions
  • There will also be a “pre” and “post” review course assessment with half the number of questions (50 questions) as the certification assessment (110 questions).

This course as well as independent study will prepare any attendee for the ABAIM AI in Medicine Assessment and Certification (110 questions in 2 hours).



Hourly Schedule

Day 1

9:00 - 10:15
Orientation to the ABAIM Artificial Intelligence in Medicine review course
I. Introduction to Artificial Intelligence
II. Data Science and Artificial Intelligence in the Current Era
- Basic Concepts of Artificial Intelligence (Modules 1.1-1.5) - History of Artificial Intelligence (Module 2.1) - History of Artificial Intelligence in Medicine (Module 3.1)
Speakers:
Anthony Chang
10:15 - 10:30
Short Break
10:30 - 11:30
I. Introduction to Artificial Intelligence (Continued)
- Healthcare Data and Databases (Modules 4.1-4.4)
Speakers:
Anthony Chang
11:30 - 12:30
LUNCH SESSION (Entrepreneurship in AI in Medicine and Q&A)
12:30 - 1:30
II. Data Science and Artificial Intelligence in the Current Era
-Healthcare Data and Databases (Modules 4.1-4.4)
- Machine and Deep Learning (Part I)(Modules 5.1-5.8)
Speakers:
Alfonso Limon, Anthony Chang
1:30 - 1:45
Short Break
1:45 - 3:00
II. Data Science and Artificial Intelligence in the Current Era (continued)
- Machine and Deep Learning (Part I)(Modules 5.1-5.8)
Speakers:
Alfonso Limon, Anthony Chang
3:00 - 3:30
Long Break
3:30 - 5:00
II. Data Science and Artificial Intelligence in the Current Era (continued)
- Machine and Deep Learning (Part II)(Modules 5.9-5.12)
Speakers:
Alfonso Limon, Anthony Chang
5:00 - 6:00
Networking

Day 2

9:00 - 10:15
Review of Day 1
II. Data Science and Artificial Intelligence in the Current Era
- Machine and Deep Learning (Part III)(Modules 5.13-5.17)
- Assessment of Model Performance
- Issues with Machine and Deep Learning
Speakers:
Alfonso Limon, Anthony Chang
10:15 - 10:30
Short Break
10:30 - 11:30
II. Data Science and Artificial Intelligence in the Current Era (continued)
- Other Key Concepts in Artificial Intelligence (Modules 6.1-6.4)
Speakers:
Alfonso Limon, Anthony Chang
11:30 - 12:30
Lunch Session (Ethics in AI in Healthcare)
12:30 - 1:30
III. The Current Era of Artificial Intelligence in Medicine
IV. The Future of Artificial Intelligence and Application in Medicine
- Clinician Cognition and AI in Medicine (Modules 7.1-7.6)
- Artificial Intelligence in Subspecialties (Modules 8.1-8.5)
- Key Concepts of the Future of AI (Modules 10.1-10.2)
- The Future of Artificial Intelligence in Medicine (Module 11.1)
Speakers:
Alfonso Limon, Anthony Chang, Orest Boyko
1:30 - 1:45
Short Break
1:45 - 3:00
Post-Course Assessment
Speakers:
Alfonso Limon, Anthony Chang, Orest Boyko
Anthony Chang
Anthony Chang
Chair, ABAIM
After his cardiology training at the Children’s Hospital of Philadelphia with his research interest in mathematics and chaos theory in biomedicine, Dr. Anthony Chang was an attending cardiologist in the cardiovascular intensive care unit of Boston Children’s Hospital and an assistant professor at Harvard Medical School. Throughout his career as a pediatric cardiac intensive care physician, he has been interested in applications of biomedical data to decision-making. He completed his Masters of Science (MS) in Data Science with a sub-specialization in artificial intelligence from Stanford School of Medicine. He is also a computer scientist-in-residence at Chapman University. He is currently the Chief Intelligence and Innovation Officer and Medical Director of the Heart Failure Program at Children’s Hospital of Orange County. He is the founder and medical director of the Medical Intelligence and Innovation Institute (MI3) that is supported by the Sharon Disney Lund Foundation. The institute, founded in 2015, is dedicated to the introduction and implementation of artificial intelligence in medicine and was the first institute of its kind in a hospital. He intends to build a clinician-computer scientist interface with a nascent society (the Medical Intelligence Society) and is the editor-in-chief of Intelligence-based Medicine, the accompanying journal for his book, Intelligence-Based Medicine: Artificial Intelligence and Human Cognition in Clinical Medicine and Healthcare. He is the organizing chair for Artificial Intelligence in Medicine (AIMed) meetings around the world, the largest and most comprehensive clinician-led meetings that focus on applications of artificial intelligence in medicine and the dean of the nascent American Board of Artificial Intelligence in Medicine (ABAIM).
Alfonso Limon
Alfonso Limon
Data Science Consultant
Highly effective technical director with proven accomplishments in a variety of engineering and medical applications combining mathematics, physics, and machine learning. Primarily focused on delivering state-of-the-art solutions impacting competitive business advantage– over a decade of experience building teams, designing complex data-driven projects, leading timeline-driven research programs, building milestone consensus for investors, and pitching technical goals to venture capitalists.
Orest Boyko
Orest Boyko
Co-Chair, ABAIM
Orest B. Boyko MD PhD is an American Board of Radiology board certified radiologist with an additional ABR certificate of added qualifications in Neuroradiology. Dr Boyko has been an Associate Professor since 2007 at the University of Southern California in Los Angeles, California, and currently is part of the USC Bridge Institute housed in the USC Michelson Center for Convergent Bioscience on the main campus of USC. As a radiologist, Dr Boyko as been working in the AI research community as a physician consultant since December 2013 in multi-modal mining in healthcare in the research lab of Dr Tanveer Sayeda-Mahmood in the IBM Almaden Research Center 650 Harry Road, San Jose, CA 95120 which has developed natural language processing applications to the electronic health record to assist in clinical decision support. Dr Boyko has also been since its inception involved the currently concluding IBM Healthcare Initiative in Radiology called the IBM Medical Sieve Radiology Grand Challenge in initial cutting edge research development of a radiology and cardiology cognitive assistant. Recently, Dr Boyko accepted an invitation to chair the newly created Guerbet Digital Solutions AI Advisory Board and Guerbet initiate to create an AI community in conjunction with Applied Radiology. Dr Boyko is active in advancing learning initiatives for the field of AI and machine learning. Dr Boyko has co-authored over 100 papers and book chapters in the field of radiology, neuroradiology and MRI.

Speakers

  • Alfonso Limon
    Alfonso Limon
    Data Science Consultant

    Highly effective technical director with proven accomplishments in a variety of engineering and medical applications combining mathematics, physics, and machine learning. Primarily focused on delivering state-of-the-art solutions impacting competitive business advantage– over a decade of experience building teams, designing complex data-driven projects, leading timeline-driven research programs, building milestone consensus for investors, and pitching technical goals to venture capitalists.

  • Anthony Chang
    Anthony Chang
    Chair, ABAIM

    After his cardiology training at the Children’s Hospital of Philadelphia with his research interest in mathematics and chaos theory in biomedicine, Dr. Anthony Chang was an attending cardiologist in the cardiovascular intensive care unit of Boston Children’s Hospital and an assistant professor at Harvard Medical School. Throughout his career as a pediatric cardiac intensive care physician, he has been interested in applications of biomedical data to decision-making. He completed his Masters of Science (MS) in Data Science with a sub-specialization in artificial intelligence from Stanford School of Medicine. He is also a computer scientist-in-residence at Chapman University. He is currently the Chief Intelligence and Innovation Officer and Medical Director of the Heart Failure Program at Children’s Hospital of Orange County.

    He is the founder and medical director of the Medical Intelligence and Innovation Institute (MI3) that is supported by the Sharon Disney Lund Foundation. The institute, founded in 2015, is dedicated to the introduction and implementation of artificial intelligence in medicine and was the first institute of its kind in a hospital. He intends to build a clinician-computer scientist interface with a nascent society (the Medical Intelligence Society) and is the editor-in-chief of Intelligence-based Medicine, the accompanying journal for his book, Intelligence-Based Medicine: Artificial Intelligence and Human Cognition in Clinical Medicine and Healthcare. He is the organizing chair for Artificial Intelligence in Medicine (AIMed) meetings around the world, the largest and most comprehensive clinician-led meetings that focus on applications of artificial intelligence in medicine and the dean of the nascent American Board of Artificial Intelligence in Medicine (ABAIM).

  • Brooke Newman
    Brooke Newman
    Doctor of Nursing Practice Learner

    Distinguished Doctor of Nursing Practice learner with specialization in leadership; inclusive and ethical contemporary nursing leader; member of team Nurses on Boards Coalition and local contract with ACNL. Focused on shared governance, capacity building, and collaborative practice advocacy. Lead organizational climate improvements and climate development which supports nursing excellence and Magnet accreditation. Navigate between strategic priorities and transformational leadership techniques for quality assurance. Experienced with executive business proposals, continuous improvement projects, promotion of a high reliability culture, health information systems, and global population health.

  • Flora Wan
    Flora Wan
    Neuroinformatics Lead & Research Coordinator, Holland Bloorview Kids Rehabilitation Hospital

    Dual technical and project coordinator role leading a multi-site research project focused on collecting and analyzing data on children with cerebral palsy at paediatric rehabilitation hospitals across Ontario. Passionate about the possibilities in applying data science, AI and machine learning to develop healthcare solutions that can improve the quality of life for children with disabilities.

  • Howard Lei
    Howard Lei
    Sr. Data Scientist, CHOC Children's

    A demonstrated history of working in Machine Learning and software development. Skills: Python, Spark, Keras, Tensorflow, Pytorch, deep learning, speech processing, statistical algorithms, Docker, Kubernetes, GCP, AWS, SQL, C/C++. Ph.D. in Electrical Engineering and Computer Science from UC Berkeley. US Citizen.

  • Ioannis Kakadiaris
    Ioannis Kakadiaris
    Data Science Lead

    Award-Winning Inventor, Researcher, Mentor, Leader, & Expert Witness with over 23 years’ experience delivering creative, stakeholder-informed research coupled with value-driven AI, Computer Vision and Biometrics solutions. Founded and Directed a successful Research Center showcasing the ability to drive innovation and affect commercialization through careful strategic planning. Offers a broad perspective coupled with an incisive ability to discern the essence of complicated issues and develop pragmatic strategies that attain measurable results. Leader and team builder executing on the principal that bold, disruptive and impactful research originates from inspired, focused teams. Dr. Kakadiaris’ research has been covered by numerous national media outlets, including ABC News, and CBS News, Discovery Channel, National Public Radio, and NBC News.

  • May D. Wang
    May D. Wang
    Secretary, ABAIM

    Dr. May Dongmei Wang is a full professor in the Departments of Biomedical Eng. and Electrical and Computer Eng. at Georgia Institute of Technology and Emory University. She is the Director of Biomedical Big Data Initiative, a Kavli Fellow, a Georgia Cancer Coalition Distinguished Scholar, a Wallace H. Coulter Distinguished Faculty Fellow, a Petit Institute Faculty Fellow, an AIMBE Fellow, and an IAMBE Fellow. She was 2018-2020 Carol Ann and David D. Flanagan Faculty Fellow. She earned BEng from Tsinghua University China, and MS/PhD from Georgia Institute of Technology.

    Dr. Wang works in Biomedical Big Data Analytics and AI, with a focus on Biomedical and Health Informatics (BHI) for predictive, personalized, and precision health (pHealth). In FDA-organized MAQC international consortium, she led next gen sequencing RNA-Seq analytics. Dr. Wang published 250+ referred journal and conference proceeding articles with 12,000+ google scholar citations. She delivered over 240 invited and keynote lectures. She currently serves in RADx working group for COVID19.

    Dr. Wang is a recipient of Georgia Tech Outstanding Faculty Mentor Award for Undergraduate, and Emory MilliPub Award for a high-impact paper cited over 1,000 times. She was 2015-2016 IEEE Engineering in Medicine and Biology Society (EMBS) Distinguished Lecture, and was an Emerging Area Editor for PNAS.

    Dr. Wang serves as Senior Editor for IEEE Journal of Biomedical and Health Informatics, an Associate Editor for IEEE Transactions on Biomedical Engineering, and IEEE Reviews of Biomedical Engineering. She is a standing panelist for NIH BCHI, and provides reviews for NSF and multiple countries. She has helped organize ACM Bioinformatics, Computational Biology, and Health Informatics Conf., and IEEE International Conf. on Biomedical and Health Informatics since 2012, and 2016-8 Gordon Research Conf. on Advanced Health Informatics, and co-chaired 2016 IEEE EMBS Annual Conf. with 2,600+. She served in IEEE Big Data Initiative (BDI) Steering Committee, and was Vice President of IEEE EMBS, and AIMBE Nomination Committee Chair 2017-2019.

    Dr. Wang was Georgia Tech Biomedical Informatics Program Co-Director in Atlanta Clinical and Translational Science Institute, and Co-Director of Georgia-Tech Center of Bio-Imaging Mass Spectrometry. Her research has been supported by NIH, NSF, CDC, Georgia Research Alliance, Georgia Cancer Coalition, Shriners’ Hospitals for Children, Children’s Health Care of Atlanta, Enduring Heart Foundation, Coulter Foundation, Microsoft, HP, UCB, and Amazon.

  • Orest Boyko
    Orest Boyko
    Co-Chair, ABAIM

    Orest B. Boyko MD PhD is an American Board of Radiology board certified radiologist with an additional ABR certificate of added qualifications in Neuroradiology.

    Dr Boyko has been an Associate Professor since 2007 at the University of Southern California in Los Angeles, California, and currently is part of the USC Bridge Institute housed in the USC Michelson Center for Convergent Bioscience on the main campus of USC.

    As a radiologist, Dr Boyko as been working in the AI research community as a physician consultant since December 2013 in multi-modal mining in healthcare in the research lab of Dr Tanveer Sayeda-Mahmood in the IBM Almaden Research Center 650 Harry Road, San Jose, CA 95120 which has developed natural language processing applications to the electronic health record to assist in clinical decision support. Dr Boyko has also been since its inception involved the currently concluding IBM Healthcare Initiative in Radiology called the IBM Medical Sieve Radiology Grand Challenge in initial cutting edge research development of a radiology and cardiology cognitive assistant.

    Recently, Dr Boyko accepted an invitation to chair the newly created Guerbet Digital Solutions AI Advisory Board and Guerbet initiate to create an AI community in conjunction with Applied Radiology.

    Dr Boyko is active in advancing learning initiatives for the field of AI and machine learning.

    Dr Boyko has co-authored over 100 papers and book chapters in the field of radiology, neuroradiology and MRI.

  • Robert Hoyt
    Robert Hoyt
    Clinical Lead

    Robert Hoyt MD received his undergraduate education at the University of Virginia and his medical education at Virginia Commonwealth University. While still on active duty in the US Navy he became involved with multiple implementations of health information technology. As a result of this experience and additional education at Stanford University, he created a Medical (Health) Informatics program at the University of West Florida in 2004. He noted early on that there were no current and practical textbooks on the subject, so he launched Health Informatics: Practical Guide in 2007. The seventh edition was published in 2018 and he just released his latest textbook Introduction to Biomedical Data Science in late 2019.

    Dr. Hoyt has also been involved with clinical and informatics research over the past decade and he has published and lectured extensively in these areas. He is a reviewer for multiple medical and informatics journals He became board certified in Clinical Informatics in 2015 and a Fellow of the American Medical Informatics Association in 2019.

    He is also involved in multiple community-oriented projects. He and his wife are a Big Couple for a local teenager, and both are Take Stock in Children mentors in the public-school system. They have supported two college scholarships annually for many years. Bob is the President of the Robert E Mitchell Foundation that supports Vietnam era prisoner of war research in Pensacola.

  • Sonia Gupta
    Sonia Gupta
    Treasurer, ABAIM

    Physician leader with expertise in healthcare Artificial Intelligence, diagnostic radiology (MRI/US/CT/X-ray), image guided procedures, digital health, regulatory requirements and FDA/CE approval, go-to-market strategies for Artificial Intelligence R&D, clinical validation, strategic planning, operations management, and M&A due diligence.

    Speaker and educator with former faculty appointments at Harvard Medical School and Temple University Hospital.

  • Tim McLerran
    Tim McLerran
    Co-Founder, Medical Intelligence One

    My mission is to care for patients based on their own deeply informative data, with wisdom derived from a partnership between human and machine intelligence, trained on data from billions of other humans.

    As a scientist, I have helped to develop and implement automated methods to measure thousands of molecules in thousands of blood samples using mass spectrometry. These thousands of molecules represent an imprint of the rich hierarchy of physiologic patterns. If the genome sets the stage, then the molecular composition of blood and other bio-specimens shines a spotlight on the actors.

    As a physician, I have seen that we treat people based on population averages, often trying many unnecessary and sometimes even harmful therapies on those who have access to care, while our system’s inefficiencies leave many others without any access to care.

    As a human, I know we can do better. This will take several key steps:

    • Build the technologies and infrastructure to:
    – Measure what matters in terms of health and disease
    – Aggregate data from enough people to leverage AI for clinical purposes

    • Build the policies and value networks necessary to:
    – Align incentives of payers and patients with the goal of long-term health

    The current state of healthcare screams for disruption. AI and big data are moving quickly to disrupt. I am taking a deep dive into the fray.