Artificial intelligence with a deep learning network for the quantification and distinction of functional adrenal tumors based on contrast-enhanced CT images

BACKGROUND: Functional adrenal tumors (FATs) are mainly diagnosed by biochemical analysis. Traditional imaging tests have limitations and cannot be used alone to diagnose FATs. In this study, we aimed to establish an artificially intelligent diagnostic model based on computed tomography (CT) images...

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Detalles Bibliográficos
Autores principales: Alimu, Parehe, Fang, Chen, Han, Yingnan, Dai, Jun, Xie, Chunmei, Wang, Jiyong, Mao, Yongxin, Chen, Yunmeng, Yao, Lu, Lv, Chuanfeng, Xu, Danfeng, Xie, Guotong, Sun, Fukang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10102777/
https://www.ncbi.nlm.nih.gov/pubmed/37064374
http://dx.doi.org/10.21037/qims-22-539

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10102777/
https://www.ncbi.nlm.nih.gov/pubmed/37064374
http://dx.doi.org/10.21037/qims-22-539

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