Extracting Clinical Information From Japanese Radiology Reports Using a 2-Stage Deep Learning Approach: Algorithm Development and Validation

BACKGROUND: Radiology reports are usually written in a free-text format, which makes it challenging to reuse the reports. OBJECTIVE: For secondary use, we developed a 2-stage deep learning system for extracting clinical information and converting it into a structured format. METHODS: Our system main...

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Detalles Bibliográficos
Autores principales: Sugimoto, Kento, Wada, Shoya, Konishi, Shozo, Okada, Katsuki, Manabe, Shirou, Matsumura, Yasushi, Takeda, Toshihiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications Inc 2023
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10686535/
https://www.ncbi.nlm.nih.gov/pubmed/37991979
http://dx.doi.org/10.2196/49041

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10686535/
https://www.ncbi.nlm.nih.gov/pubmed/37991979
http://dx.doi.org/10.2196/49041

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