Deep learning for intelligent diagnosis in thyroid scintigraphy

OBJECTIVE: To construct deep learning (DL) models to improve the accuracy and efficiency of thyroid disease diagnosis by thyroid scintigraphy. METHODS: We constructed DL models with AlexNet, VGGNet, and ResNet. The models were trained separately with transfer learning. We measured each model’s perfo...

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Detalles Bibliográficos
Autores principales: Qiao, Tingting, Liu, Simin, Cui, Zhijun, Yu, Xiaqing, Cai, Haidong, Zhang, Huijuan, Sun, Ming, Lv, Zhongwei, Li, Dan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Retrospective Clinical Research Report
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812409/
https://www.ncbi.nlm.nih.gov/pubmed/33445994
http://dx.doi.org/10.1177/0300060520982842

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812409/
https://www.ncbi.nlm.nih.gov/pubmed/33445994
http://dx.doi.org/10.1177/0300060520982842

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