activity
20242026
most citedGREEN: Generative Radiology Report Evaluation and Error Notation

42 citations · 75 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2026

CheXTemporal: A Dataset for Temporally-Grounded Reasoning in Chest Radiography

Eva Prakash, Yunhe Gao, Chong Wang +10

Chest radiograph interpretation requires temporal reasoning over prior and current studies, yet most vision-language models are trained on static image-report pairs and lack explic…

cs.CV2026

A Reasoning-Enabled Vision-Language Foundation Model for Chest X-ray Interpretation

Yabin Zhang, Chong Wang, Yunhe Gao +19

Chest X-rays (CXRs) are among the most frequently performed imaging examinations worldwide, yet rising imaging volumes increase radiologist workload and the risk of diagnostic erro…

cs.LG2026★ 1 cited

MedFeat: Model-Aware and Explainability-Driven Feature Engineering with LLMs for Tabular Prediction

Zizheng Zhang, Yiming Li, Justin Xu +6

In clinical tabular prediction, classical machine learning models with feature engineering often outperform neural methods. LLMs are increasingly used to automate this process, act…

cs.CL2025

Automated Structured Radiology Report Generation

Jean-Benoit Delbrouck, Justin Xu, Johannes Moll +11

Automated radiology report generation from chest X-ray (CXR) images has the potential to improve clinical efficiency and reduce radiologists' workload. However, most datasets, incl…

cs.CV2024★ 1 cited

CheXalign: Preference fine-tuning in chest X-ray interpretation models without human feedback

Dennis Hein, Zhihong Chen, Sophie Ostmeier +8

Radiologists play a crucial role in translating medical images into actionable reports. However, the field faces staffing shortages and increasing workloads. While automated approa…

cs.CL2024★ 5 cited

Overview of the First Shared Task on Clinical Text Generation: RRG24 and "Discharge Me!"

Justin Xu, Zhihong Chen, Andrew Johnston +9

Recent developments in natural language generation have tremendous implications for healthcare. For instance, state-of-the-art systems could automate the generation of sections in…

cs.LG2024

ACES: Automatic Cohort Extraction System for Event-Stream Datasets

Justin Xu, Jack Gallifant, Alistair E. W. Johnson +1

Reproducibility remains a significant challenge in machine learning (ML) for healthcare. Datasets, model pipelines, and even task or cohort definitions are often private in this fi…

cs.CL2024★ 42 cited

GREEN: Generative Radiology Report Evaluation and Error Notation

Sophie Ostmeier, Justin Xu, Zhihong Chen +8

Evaluating radiology reports is a challenging problem as factual correctness is extremely important due to the need for accurate medical communication about medical images. Existin…

cs.CV2024★ 26 cited

A Vision-Language Foundation Model to Enhance Efficiency of Chest X-ray Interpretation

Zhihong Chen, Maya Varma, Justin Xu +20

Over 1.4 billion chest X-rays (CXRs) are performed annually due to their cost-effectiveness as an initial diagnostic test. This scale of radiological studies provides a significant…