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Reshaping Free-Text Radiology Notes Into Structured Reports With Generative Transformers
March 29, 2024, 4:47 a.m. | Laura Bergomi, Tommaso M. Buonocore, Paolo Antonazzo, Lorenzo Alberghi, Riccardo Bellazzi, Lorenzo Preda, Chandra Bortolotto, Enea Parimbelli
cs.CL updates on arXiv.org arxiv.org
Abstract: BACKGROUND: Radiology reports are typically written in a free-text format, making clinical information difficult to extract and use. Recently the adoption of structured reporting (SR) has been recommended by various medical societies thanks to the advantages it offers, e.g. standardization, completeness and information retrieval. We propose a pipeline to extract information from free-text radiology reports, that fits with the items of the reference SR registry proposed by a national society of interventional and medical radiology, …
abstract adoption advantages arxiv clinical cs.ai cs.cl extract format free generative information making medical notes radiology reporting reports retrieval standardization text transformers type
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