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
Related Links
MATCH-DICB WebsiteHelp Desk - TBD