false
OasisLMS
Login
Hamburger Menu
Catalog
OnDemand: AI for Obesity Research and Clinical Pra ...
OnDemand: AI for Obesity Research and Clinical Practice
Create Account
Availability
On-Demand
Cost
Member: $200.00
Non-Member: $250.00
Credit Offered
3.5 AMA PRA Category 1 Credits
Description:
Artificial Intelligence (AI) is revolutionizing medical practice and research, and there are more ways to use it than you think. Come to this half-day course to learn how to use AI to save time and money while improving accuracy in both research and clinical practice. Attendees will learn how to phrase clinical research questions in ways that AI requires to be able to perform tasks, what successful multi-site AI obesity projects look like, how to make data AI-ready, and what to look for when recruiting AI-trained collaborators to work on projects. Attendees will leave this course understanding how AI can be integrated into their research and how AI can be used to inform patient diagnosis and treatment.
This course is a ticketed event at the ObesityWeek conference requiring separate payment. All in-person course registrants will also receive on-demand recordings of the course at no additional fee. This half-day course confers up to 3.5 CME credits. MOC credits are not included. This and all CME events produced by The Obesity Society count towards Group One credit when applying for the American Board of Obesity Medicine exam.
Beverages are served at this event. Meals are not included. Please have breakfast before you arrive. A 15-minutebreak will happen at 10:45-11:00 am.
REGISTER FOR THIS COURSE IN THE OBESITYWEEK REGISTRATION SYSTEM.
Learning Objectives:
Learners will be able to explain what successful multi-site AI obesity research projects look like.
Learners will be able to phrase research questions in ways that AI requires to be able to perform tasks.
Learners will be able to make data AI-ready.
Learners will understand timelines and workload to develop, train, validate, and execute AI algorithms.
Learners will be able to classify and recruit AI-trained collaborators to work on projects.
Speakers:
Diana M. Thomas, PhD, FTOS
Professor of Discipline, United States Military Academy
Dr. Diana M. Thomas, PhD, is a Professor of Mathematical Sciences at the United States Military Academy at West Point and a leading researcher in mathematical modeling of nutrition and obesity. After earning her PhD from the Georgia Institute of Technology and completing a National Research Council postdoctoral fellowship, she joined Montclair State University, where she founded and directed the Center for Quantitative Obesity Research. With over 25 years of experience, Dr. Thomas has published more than 150 peer-reviewed articles, co-invented the globally implemented SmartLoss™ program for weight management, and developed over 10 open-access health calculators. She is PI of the AIDE-ML Center for the NIH Nutrition for Precision Health Consortium, associate editor of the American Journal of Clinical Nutrition, and editor for Nutrition and Diabetes and the European Journal of Clinical Nutrition. Her numerous honors include the MAA-NJ Distinguished Teaching Award (2012), the Obesity Society George Bray Founder’s Award (2015), and the AMS Mary P. Dolciani Prize for Excellence in Research (2023).
Satish Viswanath, PhD
Associate Professor, Case Western Reserve University
I am currently an Associate Professor (with tenure) in the Department of Biomedical Engineering and serve as Co-Director of the Center for AI Enabling Discovery in Disease Biology (AID2B) at Case Western Reserve University. The primary focus of my research has been developing new artificial intelligence (AI) approaches including image analytics, radiomics, and machine learning schemes; applied to problems in computer-aided diagnosis & detection, disease characterization, as well as quantitative evaluation of response to treatment; in gastrointestinal cancers and digestive diseases. The key innovation here lies in designing unique AI tools that can capture biologically relevant and clinically intuitive measurements from routinely acquired imaging (MRI, CT, PET) or digitized images of tissue specimens. Critically, to “unlock” embedded information captured by these modalities, our AI tools inform and enrich imaging measurements with spatially resolved molecular, serum, or pathologic information. This in turn enables cross-scale association between imaging, pathology, and -omics data modalities towards building more accurate and generalizable computational imaging predictors that offer improved risk stratification, disease modeling, and biological quantitation in vivo. <br>I have authored nearly 50 peer-reviewed journal publications, over 100 conference papers & abstracts, 1 book chapter, as well as delivered over 60 invited talks and panel discussions both in the US and abroad. I have 10 issued patents in the areas of medical image analysis, computer-aided diagnosis, and pattern recognition. I am an Associate Editor for 3 leading medical imaging journals, serve on Program Committees for 3 major medical image analytics conferences, and have been elected to Senior Member in the National Academy of Inventors, the IEEE, and the SPIE. In 2023, I was selected for a Fulbright Specialist Award, as a Notable in Education Leadership by Crain’s Cleveland, and for the SIIM Imaging Informatics Innovator Award. My lab’s research in colorectal cancers and digestive diseases has been funded through the DOD/CDMRP, the NIH (NCI, NIDDK, NINR, NHLBI), as well as the State of Ohio.
Chris M. Hartshorn, Phd
Section Chief, Division of Clinical Innovation, Nih
Chris Hartshorn is the chief of the Digital & Mobile Technologies Section of the Clinical and Translational Science Awards (CTSA) Program Branch within NCATS’ Division of Clinical Innovation, where he manages and coordinates programmatic and research activities relevant to the section. Prior to joining NCATS, he served as a program director in the Division of Cancer Treatment and Diagnosis at the National Cancer Institute (NCI). During his tenure at the NIH, he has guided and managed multiple programs including the NIH Academic–Industrial Partnerships, the NIH Common Fund’s Nutrition for Precision Health, powered by the All of Us Research Program, and the Bridge to Artificial Intelligence program. Through these programs, he established the AI for Multimodal Data Modeling and Bioinformatics Center and several corollary efforts. A principal focus for Hartshorn has been establishing initiatives to bring more care, to more patients remotely by way of sophisticated multimodal analytical methods, artificial intelligence (AI), and novel biomedical technologies. Prior to joining NIH, Hartshorn was a research staff member at the National Institute of Standards and Technology for projects focused on biomedical and national security applications, as well as subsequent collaborations with the U.S. Department of Defense, U.S. Department of Justice, NIH, Merck and Pfizer.
Nikhil V. Dhurandhar, PhD, FTOS
Professor and Chair, PhD, FTOS
Dr. Nikhil Dhurandhar is a physician and nutritional biochemist. He has been in the field of obesity treatment, clinical trials and basic science studies since 1983. He is a past president of the obesity society, Editor-In-Chief of the International Journal of Obesity, and Chair of the Department of Nutritional Sciences and Associate Dean at Texas Tech University, Lubbock, TX.
Nicholas J. Clark, PhD
Associate Professor, West Point
Dr. Nick Clark received his PhD from Iowa State University in 2018. He has spent the last 6 years as an Associate Professor in Statistics and Data Science at the United States Military Academy where his focus is on program evaluation.
Leanne M. Redman, PhD, FTOS
Professor, University Of Sydney
Professor Leanne M. Redman, FTOS is the Academic Director of the Charles Perkins Centre, where she leads the Centre’s mission to improve global health through innovative, interdisciplinary research. An internationally recognised scientist in nutrition, metabolism, and obesity, Professor Redman is known for her leadership in building large-scale research enterprises and fostering collaborative scientific communities.<br>Prior to joining the Charles Perkins Centre, Professor Redman was the Director of the Pennington–Louisiana Nutrition and Obesity Research Center (NORC)—one of only 11 Centers in the United States funded by the National Institutes of Health dedicated to advancing research in nutrition and obesity. Under her leadership, the NORC supported a thriving community of 215 research scientists and fellows and stewarded a US$68.5 million research portfolio, strengthening its position as a national hub for metabolic and nutritional science.<br>Professor Redman’s scientific expertise spans human energy metabolism, weight-loss physiology, maternal and infant health, and clinical trials aimed at improving metabolic outcomes across the lifespan. Her work has contributed foundational insights into caloric restriction, pregnancy health, and lifestyle interventions, influencing both clinical practice and public health guidelines.
Course Accreditation
The Obesity Society is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.
The Obesity Society designates this enduring material for a maximum of 3.5 AMA PRA Category 1 Creditâ„¢. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
ACCME Activity ID 202790170
Important Dates
Date of Release: January 1, 2025
Date of Termination: December 31, 2027
Commercial Support
No commercial support was received for this activity.
Speaker Disclosures
Chirra, Prathyush, PhD: No relevant financial relationships
Clark, Nicholas, PhD: No relevant financial relationships
Dhurandhar, Nikhil, MS, LCEH, PhD, FTOS: Advisor relationship with Medifast (Medical Food). Researcher relationship with Novo Nordisk (Pharmaceuticals).
Hartshorn, Christopher, PhD: No relevant financial relationships
Redman, Leanne, PhD, FTOS: No relevant financial relationships
Thomas, Diana, PhD, FTOS: No relevant financial relationships
Planner Disclosures
Redman, Leanne, PhD, FTOS: No relevant financial relationships
Thomas, Diana, PhD, FTOS: No relevant financial relationships
Reviewer Disclosures
No members of the TOS CME Oversight Committee, charged with the resolution of all relevant conflicts of interest, had any relevant financial relationships while serving on the committee.
Bibliography
1. Transforming Big Data into AI-ready data for nutrition and obesity research, Obesity 2024.
2. Accreditation Board for Engineering and Technology (ABET) Criteria for Accrediting Computing Programs, 2023 – 2024 https://www.abet.org/wp-content/uploads/2023/05/C001_CAC-Criteria_2023-2024.pdf
3. Wu E, Wu K, Daneshjou R, Ouyang D, Ho DE, Zou J. How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals. Nature Medicine. 2021;27(4):582-584.
4. Shao D, Dai Y, Li N, et al. Artificial intelligence in clinical research of cancers. Briefings in Bioinformatics. 2021;23(1).
5. Thomas DM, Kleinberg S, Brown AW, Crow M, Bastian ND, Reisweber N, Lasater R, Kendall T, Shafto P, Blaine R, Smith S, Ruiz D, Morrell C, Clark N. Machine learning modeling practices to support the principles of AI and ethics in nutrition research. Nutr Diabetes. 2022 Dec 2;12(1):48.
×
OnDemand: AI for Obesity Research and Clinical Practice Course List
Login
×
Please select your language
1
English