9 papers
Lunguage: A Benchmark for Structured and Sequential Chest X-ray Interpretation
Jong Hak Moon, Geon Choi, Paloma Rabaey +10
Radiology reports convey detailed clinical observations and capture diagnostic reasoning that evolves over time. However, existing evaluation methods are limited to single-report s…
Comprehensive language-image pre-training for 3D medical image understanding
Tassilo Wald, Ibrahim Ethem Hamamci, Yuan Gao +14
In the 3D medical image domain, vision-language pre-training is used to create vision-language encoders (VLEs) that can support radiologists by retrieving patients with similar abn…
The Illusion of Readiness in Health AI
Yu Gu, Jingjing Fu, Xiaodong Liu +29
Large language models have demonstrated remarkable performance in a wide range of medical benchmarks. Yet underneath the seemingly promising results lie salient growth areas, espec…
Closing the Performance Gap Between AI and Radiologists in Chest X-Ray Reporting
Harshita Sharma, Maxwell C. Reynolds, Valentina Salvatelli +26
AI-assisted report generation offers the opportunity to reduce radiologists' workload stemming from expanded screening guidelines, complex cases and workforce shortages, while main…
NOVA: An Agentic Framework for Automated Histopathology Analysis and Discovery
Anurag J. Vaidya, Felix Meissen, Daniel C. Castro +7
Digitized histopathology analysis involves complex, time-intensive workflows and specialized expertise, limiting its accessibility. We introduce NOVA, an agentic framework that tra…
Data Scaling Laws for Radiology Foundation Models
Maximilian Ilse, Harshita Sharma, Anton Schwaighofer +12
Foundation vision encoders such as CLIP and DINOv2, trained on web-scale data, exhibit strong transfer performance across tasks and datasets. However, medical imaging foundation mo…