1 citations · 1 across the 5 of their papers we have counts for
5 papers
Lesion Detection in CT with Frozen Self-Distilled Features: SALT, a Spatially Adaptive Label-Guided Temperature
Mahmut S. Gokmen, Evan W. Damron, Mitchell A. Klusty +3
Self-supervised pretraining objectives are spatially uniform: the teacher temperature and the per-patch loss weight are identical everywhere in the image, so a lesion a few patches…
DALE-CT: Depth-Aware 2D Slice Encoders Learn an Anatomical World Model of Chest CT
Evan W. Damron, Mahmut S. Gokmen, Mitchell A. Klusty +3
Chest CT is among the highest-volume imaging exams in medicine, yet expert voxel-level annotations are scarce and costly, motivating encoders that learn directly from unlabeled sca…
A Framework for Cross-Domain Generalization in Coronary Artery Calcium Scoring Across Gated and Non-Gated Computed Tomography
Mahmut S. Gokmen, Moneera N. Haque, Steve W. Leung +6
Coronary artery calcium (CAC) scoring is a key predictor of cardiovascular risk, but it relies on ECG-gated CT scans, restricting its use to specialized cardiac imaging settings. W…
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…
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…