Clip in medical imaging: A comprehensive survey

Z Zhao, Y Liu, H Wu, M Wang, Y Li, S Wang… - ar** review of using large language models (LLMs) to investigate electronic health records (EHRs)
L Li, J Zhou, Z Gao, W Hua, L Fan, H Yu… - arxiv preprint arxiv …, 2024 - arxiv.org
Electronic Health Records (EHRs) play an important role in the healthcare system. However,
their complexity and vast volume pose significant challenges to data interpretation and …

Chexagent: Towards a foundation model for chest x-ray interpretation

Z Chen, M Varma, JB Delbrouck, M Paschali… - arxiv preprint arxiv …, 2024 - arxiv.org
Chest X-rays (CXRs) are the most frequently performed imaging test in clinical practice.
Recent advances in the development of vision-language foundation models (FMs) give rise …

Mdagents: An adaptive collaboration of llms for medical decision-making

Y Kim, C Park, H Jeong, YS Chan… - Advances in …, 2025 - proceedings.neurips.cc
Foundation models are becoming valuable tools in medicine. Yet despite their promise, the
best way to leverage Large Language Models (LLMs) in complex medical tasks remains an …

Ehragent: Code empowers large language models for few-shot complex tabular reasoning on electronic health records

W Shi, R Xu, Y Zhuang, Y Yu, J Zhang, H Wu… - arxiv preprint arxiv …, 2024 - arxiv.org
Large language models (LLMs) have demonstrated exceptional capabilities in planning and
tool utilization as autonomous agents, but few have been developed for medical problem …

EHRNoteQA: An LLM Benchmark for Real-World Clinical Practice Using Discharge Summaries

S Kweon, J Kim, H Kwak, D Cha… - Advances in …, 2025 - proceedings.neurips.cc
Abstract Discharge summaries in Electronic Health Records (EHRs) are crucial for clinical
decision-making, but their length and complexity make information extraction challenging …

BlendSQL: A scalable dialect for unifying hybrid question answering in relational algebra

P Glenn, PP Dakle, L Wang, P Raghavan - arxiv preprint arxiv …, 2024 - arxiv.org
Many existing end-to-end systems for hybrid question answering tasks can often be boiled
down to a" prompt-and-pray" paradigm, where the user has limited control and insight into …

GEMeX: A Large-Scale, Groundable, and Explainable Medical VQA Benchmark for Chest X-ray Diagnosis

B Liu, K Zou, L Zhan, Z Lu, X Dong, Y Chen… - arxiv preprint arxiv …, 2024 - arxiv.org
Medical Visual Question Answering (VQA) is an essential technology that integrates
computer vision and natural language processing to automatically respond to clinical …

SM3-Text-to-Query: Synthetic Multi-Model Medical Text-to-Query Benchmark

S Sivasubramaniam, C Osei-Akoto, Y Zhang… - arxiv preprint arxiv …, 2024 - arxiv.org
Electronic health records (EHRs) are stored in various database systems with different
database models on heterogeneous storage architectures, such as relational databases …

Enhancing human-computer interaction in chest x-ray analysis using vision and language model with eye gaze patterns

Y Kim, J Wu, Y Abdulle, Y Gao, H Wu - International Conference on …, 2024 - Springer
Abstract Recent advancements in Computer Assisted Diagnosis have shown promising
performance in medical imaging tasks, particularly in chest X-ray analysis. However, the …