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20242026
most citedMerlin: A Computed Tomography Vision-Language Foundation Model and Dataset

23 citations · 23 across the 2 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

eess.IV2025

Patch-Based Diffusion for Data-Efficient, Radiologist-Preferred MRI Reconstruction

Rohan Sanda, Asad Aali, Andrew Johnston +3

Magnetic resonance imaging (MRI) requires long acquisition times, raising costs, reducing accessibility, and making scans more susceptible to motion artifacts. Diffusion probabilis…

eess.IV2025

Evaluating and Improving the Effectiveness of Synthetic Chest X-Rays for Medical Image Analysis

Eva Prakash, Jeya Maria Jose Valanarasu, Zhihong Chen +9

Purpose: To explore best-practice approaches for generating synthetic chest X-ray images and augmenting medical imaging datasets to optimize the performance of deep learning models…

cs.CV2025

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.CL2025

Zero-shot Performance of Generative AI in Brazilian Portuguese Medical Exam

Cesar Augusto Madid Truyts, Amanda Gomes Rabelo, Gabriel Mesquita de Souza +7

Artificial intelligence (AI) has shown the potential to revolutionize healthcare by improving diagnostic accuracy, optimizing workflows, and personalizing treatment plans. Large La…

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.CL2025

MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks

Suhana Bedi, Hejie Cui, Miguel Fuentes +78

While large language models (LLMs) achieve near-perfect scores on medical licensing exams, these evaluations inadequately reflect the complexity and diversity of real-world clinica…