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Report length distribution in train, test and validation split

Report length distribution in train, test and validation split

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Fig. 1 Proposed methodology for automated X-ray interpretation
Fig. 2 Sample X-ray images and corresponding findings in the form of...
Fig. 3 Distribution of report length in number of words
Fig. 4 Report length distribution in train, test and validation split
+6 Fig. 8 Training vs Validation Loss of ViT B16-BART Model
Vision-Language Models for Automated Chest X-ray Interpretation: Leveraging ViT and GPT-2
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  • Jan 2025
Radiology plays a pivotal role in modern medicine due to its non-invasive diagnostic capabilities. However, the manual generation of unstructured medical reports is time consuming and prone to errors. It creates a significant bottleneck in clinical workflows. Despite advancements in AI-generated radiology reports, challenges remain in achieving det...
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