5 papers
Phrase-grounded Fact-checking for Automatically Generated Chest X-ray Reports
Razi Mahmood, Diego Machado-Reyes, Joy Wu +7
With the emergence of large-scale vision language models (VLM), it is now possible to produce realistic-looking radiology reports for chest X-ray images. However, their clinical tr…
Anatomically-Grounded Fact Checking of Automated Chest X-ray Reports
R. Mahmood, K. C. L. Wong, D. M. Reyes +8
With the emergence of large-scale vision-language models, realistic radiology reports may be generated using only medical images as input guided by simple prompts. However, their p…
Evaluating Automated Radiology Report Quality through Fine-Grained Phrasal Grounding of Clinical Findings
Razi Mahmood, Pingkun Yan, Diego Machado Reyes +5
Several evaluation metrics have been developed recently to automatically assess the quality of generative AI reports for chest radiographs based only on textual information using l…
Fact-Checking of AI-Generated Reports
Razi Mahmood, Diego Machado Reyes, Ge Wang +2
With advances in generative artificial intelligence (AI), it is now possible to produce realistic-looking automated reports for preliminary reads of radiology images. This can expe…
Spatially-Preserving Flattening for Location-Aware Classification of Findings in Chest X-Rays
Neha Srivathsa, Razi Mahmood, Tanveer Syeda-Mahmood
Chest X-rays have become the focus of vigorous deep learning research in recent years due to the availability of large labeled datasets. While classification of anomalous findings…