activity
20232026
most citedLeveraging LLMs for Structured Data Extraction from Unstructured Patient Records

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

Curriculum-Driven 3D CT Report Generation via Language-Free Visual Grafting and Zone-Constrained Compression

V. K. Cody Bumgardner, Mitchell A. Klusty, Mahmut S. Gokmen +1

Automated radiology report generation from 3D computed tomography (CT) volumes is challenging due to extreme sequence lengths, severe class imbalance, and the tendency of large lan…

cs.AI2025★ 1 cited

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…

cs.HC2023

SmartState: An Automated Research Protocol Adherence System

Samuel E. Armstrong, Mitchell A. Klusty, Aaron D. Mullen +2

Developing and enforcing study protocols is crucial in medical research, especially as interactions with participants become more intricate. Traditional rules-based systems struggl…