ABAIM Advanced Course


Apr 08 - 09 2022


9:00 am - 5:00 pm

The ABAIM AI in Medicine Advanced Course is a comprehensive, two-day course on advanced 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 designed for graduates of the ABAIM Introductory Course as well as attendees who are familiar with basic AI and data science concepts.

This course will provide a more in-depth look at concepts such as:

  • Bayes' Theorem
  • Federated Learning
  • Digital Twins
  • How to review a paper
  • And more

About the advanced course:

  • Similar to the Introductory 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
  • This course will prepare you for the Advanced Educational Certification

Register Now

Course Registration
CEO, Physician, Student, etc
Hospital, School, Company, etc

This email and password will be used to access all ABAIM course materials

Already have an ABAIM account? Log in now

Please select the option that most closely describes you



Credit Card *
Address *

Hourly Schedule

Day 1 (All times EDT)

9:00 - 10:15
Orientation and Introductions
10:15 - 10:30
Short Break
10:30 - 11:30
Introduction to Advanced Concepts in Artificial Intelligence
11:30 - 12:30
Lunch Session
AI Entrepreneurship and Economics
12:30 - 1:30
Advanced Data Science in the Current Era
1:30 - 1:45
Short Break
1:45 - 3:00
Advanced Data Science in the Current Era (Continued)
3:00 - 3:30
Long Break
3:30 - 5:00
Advanced Data Science in the Current Era (Continued)
5:00 - 6:00

Day 2 (All times EDT)

10:00 - 11:15
Review of Day 1 Advanced Data Science in the Current Era (Continued)
11:15 - 11:30
Short Break
11:30 - 12:30
Advanced Data Science in the Current Era (Continued)
12:30 - 1:30
Lunch Session
How To Review a AI in Medicine Paper
1:30 - 2:30
The Future of Advanced Artificial Intelligence and Application in Medicine
2:30 - 2:45
Short Break
2:45 - 4:00
AI in Medicine Demonstration and Final Q&A


  • 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).

  • 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 Wallace H. Coulter Distinguished Faculty Fellow and full professor in Biomedical Engineering Dept. and School of Electrical and Computer Engineering at Georgia Institute of Technology (GT) and Emory University (EU). She is Director of Biomedical Big Data Initiative, Georgia Distinguished Cancer Scholar, Petit Institute Faculty Fellow, Kavli Fellow, AIMBE Fellow, IAMBE Fellow, IEEE Fellow, and Board of Directors in American Board of AI in Medicine. Dr. Wang received BEng from Tsinghua University China, and MS with PhD degrees from Georgia Tech. Her research is in Biomedical Big Data with AI-Driven Intelligent Reality (IR) for predictive, personalized, and precision health (pHealth). During 20+ years academic professorship and ~4 years industrial research, she published 270+ articles in referred journals and conference proceedings and delivered 260+ invited and keynote lectures. She is a recipient of Georgia Tech (GT) Outstanding Faculty Mentor Award and Emory University MilliPub Award (for a high-impact paper that is cited over 1,000 times). She organized IEEE Healthcare Summit on Integrating BHI and AI to Combat Pandemics, and IEEE-JBHI Special Issue on AI-driven Informatics, Sensing, Imaging and Big Data Analytics for Fighting the COVID-19 Pandemic.

    Dr. Wang is the Senior Editor for IEEE Journal of Biomedical & Health Informatics (J-BHI, Impact Factor 7.02), an Associate Editor for IEEE Transactions for BME, and IEEE Reviews for BME, a panelist for NIH CDMA Study Section, NSF Smart and Connect Health, Brain Canada, and multiple European countries. She was Emerging Area Editor for Proceedings of National Academy of Sciences (PNAS), 2014-2015 IEEE Engineering in Medicine and Biology Society (EMBS) Distinguished Lecturer, and was elected EMBS Vice Presidents twice. Dr. Wang has dedicated to growing Biomedical and Health Informatics (BHI) community and is chairing IEEE Biomedical and Health Informatics Technical Community and ACM Special Interest Group in Bioinformatics. She serves in IEEE Future Directions Committee and International Academy of Medical and Biological Engineering (IAMBE) Executive Committee.

    At Georgia Tech, Dr. Wang is in 2022 President Leading Women Program and 2021 Provost Emerging Leaders Program. She was 2018-2021 Carol Ann and David Flanagan Distinguished Faculty Fellow, 2015-2017 GT Biomedical Informatics Program Co-Director in Atlanta Clinical and Translational Science Institute (ACTSI). Before 2016, Dr. Wang was Director of Bioinformatics and Biocomputing Core in NIH/NCI-sponsored U54 Center for Cancer Nanotechnology Excellence, and Co-Director of GT Center of Bio-Imaging Mass Spectrometry for over 10 years. Dr. Wang’s research has been supported by NIH, NSF, CDC, VA, Georgia Research Alliance, Georgia Cancer Coalition, Shriners’ Hospitals for Children, Children’s Health Care of Atlanta, Enduring Heart Foundation, Coulter Foundation, Microsoft Research, 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.

  • Richard Frank
    Richard Frank
    Chief Medical Officer at Siemens Healthineers

    30 years’ success in regulatory labeling of, public and private payment for, and clinical adoption of therapeutic and diagnostic drugs and devices worldwide, based on diverse and growing skillsets, domain knowledge, and network.

    Proven skillset includes design and conduct of clinical trials programs from phase I to post-market registries, preparation and presentation of summary reports of safety and efficacy, and leadership of product teams in development and implementation of strategy and tactics vis-à-vis regulators, payers, professional societies, and patient advocates. I am particularly adept at persuasive deployment of clinical and economic evidence to decision-makers and key influencers, credibly asserting the safety, efficacy, reasonableness, necessity, and economic benefits of the product or service. The result has been growth in the appropriate use of novel therapeutic and diagnostic products, alone or in combination.

    Persuasive deployment of evidence is also evidenced by my success in reforming national barriers to labeling, coverage, and adoption in clinical practice including pilot projects, public-private partnerships, and import-export matters (eg serialization and quality assurance). The result is growth in the capacity of healthcare delivery systems to deliver quality care, broader access by patients in need, and growth of whole markets in the US, Brazil, Chile, India, Canada, China, Central America, and Eastern Europe.

    The credibility and network accruing to 3 decades’ pursuit of objectives shared among stakeholders in industry, academia, NGOs, and government agencies has facilitated my opinion leadership in clinical evidentiary standards and related matters of government policy.

    These skillsets, domain knowledge, and networks qualify me to address product-, market-, or delivery system-specific inefficiencies and issues which burden payers and inhibit patients’ access to the benefits of innovation in products and services.

  • 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.

Event Registration