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20242026
most citedEnhancing disease detection in radiology reports through fine-tuning lightweight LLM on weak labels

4 citations · 13 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV2026

MonteRET: AI Agent Enhancing Multimodal LLMs with Multi-granularity Knowledge Retrieval for Chest CT Report Generation

Yi Lin, Yihao Ding, Elana Benishay +8

Automated chest CT report generation remains challenging because clinically faithful reporting requires both whole-volume understanding and accurate description of localized anatom…

cs.CL2026

Budget-Aware Routing for Long Clinical Text

Khizar Qureshi, Geoffrey Martin, Yifan Peng

A key challenge for large language models is token cost per query and overall deployment cost. Clinical inputs are long, heterogeneous, and often redundant, while downstream tasks…

cs.CV2026

Establishing dermatopathology encyclopedia DermpathNet with Artificial Intelligence-Based Workflow

Ziyang Xu, Mingquan Lin, Yiliang Zhou +6

Accessing high-quality, open-access dermatopathology image datasets for learning and cross-referencing is a common challenge for clinicians and dermatopathology trainees. To establ…

cs.CL2026

RSNA Large Language Model Benchmark Dataset for Chest Radiographs of Cardiothoracic Disease: Radiologist Evaluation and Validation Enhanced by AI Labels (REVEAL-CXR)

Yishu Wei, Adam E. Flanders, Errol Colak +35

Multimodal large language models have demonstrated comparable performance to that of radiology trainees on multiple-choice board-style exams. However, to develop clinically useful…

cs.CL2025★ 1 cited

A Multi-agent Large Language Model Framework to Automatically Assess Performance of a Clinical AI Triage Tool

Adam E. Flanders, Yifan Peng, Luciano Prevedello +6

Purpose: The purpose of this study was to determine if an ensemble of multiple LLM agents could be used collectively to provide a more reliable assessment of a pixel-based AI triag…

cs.AI2025

Enhancing Health Fact-Checking with LLM-Generated Synthetic Data

Jingze Zhang, Jiahe Qian, Yiliang Zhou +1

Fact-checking for health-related content is challenging due to the limited availability of annotated training data. In this study, we propose a synthetic data generation pipeline t…

cs.CL2025★ 1 cited

Generative Large Language Models Trained for Detecting Errors in Radiology Reports

Cong Sun, Kurt Teichman, Yiliang Zhou +8

In this retrospective study, a dataset was constructed with two parts. The first part included 1,656 synthetic chest radiology reports generated by GPT-4 using specified prompts, w…

cs.CL2025★ 2 cited

MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs

Juncheng Wu, Wenlong Deng, Xingxuan Li +12

Medical tasks such as diagnosis and treatment planning require precise and complex reasoning, particularly in life-critical domains. Unlike mathematical reasoning, medical reasonin…

cs.CL2025

A foundation model for human-AI collaboration in medical literature mining

Zifeng Wang, Lang Cao, Qiao Jin +20

Systematic literature review is essential for evidence-based medicine, requiring comprehensive analysis of clinical trial publications. However, the application of artificial intel…

cs.AI2024★ 4 cited

Enhancing disease detection in radiology reports through fine-tuning lightweight LLM on weak labels

Yishu Wei, Xindi Wang, Hanley Ong +4

Despite significant progress in applying large language models (LLMs) to the medical domain, several limitations still prevent them from practical applications. Among these are the…

cs.CV2024★ 4 cited

GSCo: Towards Generalizable AI in Medicine via Generalist-Specialist Collaboration

Sunan He, Yuxiang Nie, Hongmei Wang +21

Generalist foundation models (GFMs) are renowned for their exceptional capability and flexibility in effectively generalizing across diverse tasks and modalities. In the field of m…

cs.CL2024★ 1 cited

Uncovering Misattributed Suicide Causes through Annotation Inconsistency Detection in Death Investigation Notes

Song Wang, Yiliang Zhou, Ziqiang Han +5

Data accuracy is essential for scientific research and policy development. The National Violent Death Reporting System (NVDRS) data is widely used for discovering the patterns and…

eess.IV2024

Evaluating GPT-4 with Vision on Detection of Radiological Findings on Chest Radiographs

Yiliang Zhou, Hanley Ong, Patrick Kennedy +6

The study examines the application of GPT-4V, a multi-modal large language model equipped with visual recognition, in detecting radiological findings from a set of 100 chest radiog…