1 citations · 1 across the 3 of their papers we have counts for
5 papers
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…
Insights into a radiology-specialised multimodal large language model with sparse autoencoders
Kenza Bouzid, Shruthi Bannur, Felix Meissen +4
Interpretability can improve the safety, transparency and trust of AI models, which is especially important in healthcare applications where decisions often carry significant conse…
MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models
Harshita Sharma, Valentina Salvatelli, Shaury Srivastav +13
There is growing interest in applying AI to radiology report generation, particularly for chest X-rays (CXRs). This paper investigates whether incorporating pixel-level information…
PadChest-GR: A Bilingual Chest X-ray Dataset for Grounded Radiology Report Generation
Daniel C. Castro, Aurelia Bustos, Shruthi Bannur +11
Radiology report generation (RRG) aims to create free-text radiology reports from clinical imaging. Grounded radiology report generation (GRRG) extends RRG by including the localis…