400 citations · 519 across the 7 of their papers we have counts for
7 papers
A Study of Generative Large Language Model for Medical Research and Healthcare
Cheng Peng, Xi Yang, Aokun Chen +16
There is enormous enthusiasm and concerns in using large language models (LLMs) in healthcare, yet current assumptions are all based on general-purpose LLMs such as ChatGPT. This s…
Machine Learning Methods Applied to Cortico-Cortical Evoked Potentials Aid in Localizing Seizure Onset Zones
Ian G. Malone, Kaleb E. Smith, Morgan E. Urdaneta +5
Epilepsy affects millions of people, reducing quality of life and increasing risk of premature death. One-third of epilepsy cases are drug-resistant and require surgery for treatme…
Conditional generation of cloud fields
Naser G. A. Mahfouz, Yi Ming, Kaleb Smith
Processes related to cloud physics constitute the largest remaining scientific uncertainty in climate models and projections. This uncertainty stems from the coarse nature of curre…
GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records
Xi Yang, Aokun Chen, Nima PourNejatian +15
There is an increasing interest in developing artificial intelligence (AI) systems to process and interpret electronic health records (EHRs). Natural language processing (NLP) powe…
Building an AI-ready RSE Workforce
Ying Zhang, Matthew A. Gitzendanner, Dan S. Maxwell +6
Artificial Intelligence has been transforming industries and academic research across the globe, and research software development is no exception. Machine learning and deep learni…
A Spectral Enabled GAN for Time Series Data Generation
Kaleb E. Smith, Anthony O. Smith
Time dependent data is a main source of information in today's data driven world. Generating this type of data though has shown its challenges and made it an interesting research a…
Conditional GAN for timeseries generation
Kaleb E Smith, Anthony O Smith
It is abundantly clear that time dependent data is a vital source of information in the world. The challenge has been for applications in machine learning to gain access to a consi…