15 citations · 36 across the 10 of their papers we have counts for
10 papers
CURE: Curriculum-guided Multi-task Training for Reliable Anatomy Grounded Report Generation
Pablo Messina, Andrés Villa, Juan León Alcázar +5
Medical vision-language models can automate the generation of radiology reports but struggle with accurate visual grounding and factual consistency. Existing models often misalign…
CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray
Mingquan Lin, Gregory Holste, Song Wang +30
The CXR-LT series is a community-driven initiative designed to enhance lung disease classification using chest X-rays (CXR). It tackles challenges in open long-tailed lung disease…
IP-CRR: Information Pursuit for Interpretable Classification of Chest Radiology Reports
Yuyan Ge, Kwan Ho Ryan Chan, Pablo Messina +1
The development of AI-based methods to analyze radiology reports could lead to significant advances in medical diagnosis, from improving diagnostic accuracy to enhancing efficiency…
Extracting and Encoding: Leveraging Large Language Models and Medical Knowledge to Enhance Radiological Text Representation
Pablo Messina, René Vidal, Denis Parra +2
Advancing representation learning in specialized fields like medicine remains challenging due to the scarcity of expert annotations for text and images. To tackle this issue, we pr…
Inspecting state of the art performance and NLP metrics in image-based medical report generation
Pablo Pino, Denis Parra, Pablo Messina +2
Several deep learning architectures have been proposed over the last years to deal with the problem of generating a written report given an imaging exam as input. Most works evalua…
A Survey on Deep Learning and Explainability for Automatic Report Generation from Medical Images
Pablo Messina, Pablo Pino, Denis Parra +7
Every year physicians face an increasing demand of image-based diagnosis from patients, a problem that can be addressed with recent artificial intelligence methods. In this context…
CuratorNet: Visually-aware Recommendation of Art Images
Pablo Messina, Manuel Cartagena, Patricio Cerda-Mardini +2
Although there are several visually-aware recommendation models in domains like fashion or even movies, the art domain lacks thesame level of research attention, despite the recent…
Do Better ImageNet Models Transfer Better... for Image Recommendation?
Felipe del Rio, Pablo Messina, Vicente Dominguez +1
Visual embeddings from Convolutional Neural Networks (CNN) trained on the ImageNet dataset for the ILSVRC challenge have shown consistently good performance for transfer learning a…
Comparing Neural and Attractiveness-based Visual Features for Artwork Recommendation
Vicente Dominguez, Pablo Messina, Denis Parra +3
Advances in image processing and computer vision in the latest years have brought about the use of visual features in artwork recommendation. Recent works have shown that visual fe…
Exploring Content-based Artwork Recommendation with Metadata and Visual Features
Pablo Messina, Vicente Dominguez, Denis Parra +2
Compared to other areas, artwork recommendation has received little attention, despite the continuous growth of the artwork market. Previous research has relied on ratings and meta…