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XFlow: A Workflow Model for Instruction-Guided Lesion Segmentation in Chest X-rays
Geon Choi, Hangyul Yoon, Hyunki Park +2
Existing text-guided segmentation models in the medical domain cover only a narrow set of anatomical structures and lesions in chest X-rays (CXRs), and most of them assume that the…
SentZero: An Enhanced Sentence-Centric Vision-Language Pretraining for Multi-Task Zero-Shot Chest X-Ray Analysis
Hangyul Yoon, Hyungyung Lee, Edward Choi +1
Vision-language (VL) pretraining using paired chest X-ray (CXR) images and radiology reports has shown strong potential for medical image understanding. However, existing methods o…
CheXpercept: A Benchmark for Evaluating Expert-Level Lesion Perception in Chest X-rays
Geon Choi, Hangyul Yoon, Nalee Kim +5
The evaluation of vision-language models (VLMs) for chest X-ray (CXR) analysis has largely been limited to disease-presence classification without visual grounding. Such evaluation…
EHRNote-ChatQA: A Benchmark for Evidence-Grounded Multi-Turn Clinical Question Answering over Longitudinal Discharge Summaries
Jiyoun Kim, Muhan Yeo, Eunhye Jang +14
Discharge summaries are crucial clinical documents containing the context of a patient's overall hospital stay, and are routinely reviewed by medical experts for patient readmissio…
TRIAGE: Dialectical LLM Reasoning for Explainable Risk Prediction on Irregularly Sampled Medical Time Series
Hyeongwon Jang, Gyouk Chu, Changhun Kim +4
Clinical early warning systems built on irregularly sampled medical time series (ISMTS) from electronic health records must deliver continuous risk scores for patient triage as wel…
CXReasonAgent: Evidence-Grounded Diagnostic Reasoning Agent for Chest X-rays
Hyungyung Lee, Hangyul Yoon, Edward Choi
Chest X-ray plays a central role in thoracic diagnosis, and its interpretation inherently requires multi-step, evidence-grounded reasoning. However, large vision-language models (L…
ECG-Reasoning-Benchmark: A Benchmark for Evaluating Clinical Reasoning Capabilities in ECG Interpretation
Jungwoo Oh, Hyunseung Chung, Junhee Lee +6
While Multimodal Large Language Models (MLLMs) show promising performance in automated electrocardiogram interpretation, it remains unclear whether they genuinely perform actual st…