5 papers
Toward an AI Reasoning-Enabled System for Patient-Clinical Trial Matching
Caroline N. Leach, Mitchell A. Klusty, Samuel E. Armstrong +6
Screening patients for clinical trial eligibility remains a manual, time-consuming, and resource-intensive process. We present a secure, scalable proof-of-concept system for Artifi…
Leveraging LLMs for Structured Data Extraction from Unstructured Patient Records
Mitchell A. Klusty, Elizabeth C. Solie, Caroline N. Leach +8
Manual chart review remains an extremely time-consuming and resource-intensive component of clinical research, requiring experts to extract often complex information from unstructu…
Vision Foundry: A System for Training Foundational Vision AI Models
Mahmut S. Gokmen, Mitchell A. Klusty, Evan W. Damron +6
Self-supervised learning (SSL) leverages vast unannotated medical datasets, yet steep technical barriers limit adoption by clinical researchers. We introduce Vision Foundry, a code…
Semantic Nutrition Estimation: Predicting Food Healthfulness from Text Descriptions
Dayne R. Freudenberg, Daniel G. Haughian, Mitchell A. Klusty +8
Accurate nutritional assessment is critical for public health, but existing profiling systems require detailed data often unavailable or inaccessible from colloquial text descripti…
Institutional Platform for Secure Self-Service Large Language Model Exploration
V. K. Cody Bumgardner, Mitchell A. Klusty, W. Vaiden Logan +5
This paper introduces a user-friendly platform developed by the University of Kentucky Center for Applied AI, designed to make large, customized language models (LLMs) more accessi…