October 31, 2024
12:15 pm – 1:15 pm
Speaker:
Tony Mangino, Department of Biostatistics, University of Kentucky
Where:
327 McVey Hall
(Zoom link: https://uky.zoom.us/j/82467171189)
Title:
An introduction to generative AI in Biomedical Applications
Abstract:
Generative AI has become ubiquitous since the advent of ChatGPT, though the underlying mechanisms are far from novel. Goodfellow’s 2014 introduction of generative adversarial networks (GANs) was a watershed moment for the generative modeling domain and has since been widely used in a wide variety of contexts. This presentation and accompanying tutorial introduce participants to a lesser-used application of GANs: Their ability to generate synthetic patient records with data largely mirroring the same data obtained from real patients. This presentation illustrates an example using data from patients admitted to UK hospitals for either Acute Coronary Syndrome (ACS) or Takotsubo Syndrome (TTS), and the resulting prediction model from the original study (published as Ahmed et al., 2024). Based on the results of this study, I showcase the ability of the RGAN package in R statistical software to generate novel patient records that closely mimic actual cases. Results from the original study and models trained on the GAN-generated synthetic cases will be compared.