ArticleFrontiers in digital health2025
ChestX-Transcribe: a multimodal transformer for automated radiology report generation from chest x-rays.
Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Verification of the impact of differences between objective and subjective evaluation methods on the interpretation of artificial intelligence systems generating mammogram reports using vision-language model.Japanese journal of radiology · 2026Article
- An Explainable Multimodal Framework for Breast Ultrasound Report Generation Using Vision-Language Transformers.Journal of imaging · 2026Article
- Automated Radiological Report Generation from Breast Ultrasound Images Using Vision and Language Transformers.Journal of imaging · 2026Article
- Hybrid framework for automated generation of mammography radiology reports.Computational and structural biotechnology journal · 2025Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiology departments are under increasing pressure to meet the demand for timely and accurate diagnostics, especially with chest x-rays, a key modality for pulmonary condition assessment. Producing comprehensive and accurate radiological reports is a time-consuming process prone to errors, particularly in high-volume clinical environments. Automated report generation plays a crucial role in alleviating radiologists' workload, improving diagnostic accuracy, and ensuring consistency. This paper introduces
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Registered trials
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