Improving detection of impacted animal bones on lateral neck radiograph using a deep learning artificial intelligence algorithm

OBJECTIVE: We aimed to develop a deep learning artificial intelligence (AI) algorithm to detect impacted animal bones on lateral neck radiographs and to assess its effectiveness for improving the interpretation of lateral neck radiographs. METHODS: Lateral neck radiographs were retrospectively colle...

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Detalles Bibliográficos
Autores principales: Chen, Yueh-Sheng, Luo, Sheng-Dean, Lee, Chi-Hsun, Lin, Jian-Feng, Lin, Te-Yen, Ko, Sheung-Fat, Yu, Chiun-Chieh, Chiang, Pi-Ling, Wang, Cheng-Kang, Chiu, I.-Min, Huang, Yii-Ting, Tai, Yi-Fan, Chiang, Po-Teng, Lin, Wei-Che
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10020388/
https://www.ncbi.nlm.nih.gov/pubmed/36929090
http://dx.doi.org/10.1186/s13244-023-01385-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10020388/
https://www.ncbi.nlm.nih.gov/pubmed/36929090
http://dx.doi.org/10.1186/s13244-023-01385-x

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