AIM-AHEAD and MATCH AI Hands-on Workshop Series

Welcome to the MATCH AI Hands-on Workshop Series

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Course Description

About

MATCH is part of the AIM-AHEAD Data and Infrastructure Capacity Building (DICB) Program and aims to ignite & accelerate AI and machine learning projects in biomedicine for AIM-AHEAD awardees and their teams.

Course description

This course provides a practical introduction to the use of artificial intelligence in biomedical research. Participants will explore applications of AI across diverse areas including electronic health records (EHRs), computer vision, generative AI, adaptive learning, and federated learning. Through a mix of conceptual overviews and hands-on examples, learners will gain the tools and knowledge needed to evaluate, apply, and adapt AI methods in their research.

Course learning objectives

By the end of this course, learners will be able to:

Discover new AI modalities for data classification and generation, and model deployment
Gain confidence in dealing with different data types encountered in healthcare AI, such as electronic health care records, images and text data
Recognize common pitfalls and considerations in using different techniques for data analysis

Instrumental persons

Amina Qutub - Principal Investigator
Mark Goldberg - Principal Investigator
Dhireesha Kudithipudi - Principal Investigator
Panagiotis Markopoulos - Principal Investigator
Carolina Vivas-Valencia - Collaborating Investigator
Kevin Desai - Collaborating Investigator
Mignon Frances Dumanjog - Project Coordinator
Jayanta Dey - SME
Sambit Panda - SME
Christian Cruz - SME
Paul Jaimes-Buitron - SME
Toufeeq Syed, PhD - MPI, AIM-AHEAD Coordinating Center
Deevakar Rogith, PhD - AP, UTH School of Biomedical Informatics
Lesley Grandstaff, M.Ed. - Communications Hub, AIM-AHEAD
Paul Warhurst, PhD - Communications Hub, AIM-AHEAD
Cara Morrison - Communications Hub, AIM-AHEAD

HelpDesk - TBD

Funding

The AIM-AHEAD program is funded by NIH, Agreement No. 1OT2OD032581. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.