Reducing the number of unnecessary biopsies for mammographic BI-RADS 4 lesions through a deep transfer learning method

BACKGROUND: In clinical practice, reducing unnecessary biopsies for mammographic BI-RADS 4 lesions is crucial. The objective of this study was to explore the potential value of deep transfer learning (DTL) based on the different fine-tuning strategies for Inception V3 to reduce the number of unneces...

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Detalles Bibliográficos
Autores principales: Meng, Mingzhu, Li, Hong, Zhang, Ming, He, Guangyuan, Wang, Long, Shen, Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10265786/
https://www.ncbi.nlm.nih.gov/pubmed/37312026
http://dx.doi.org/10.1186/s12880-023-01023-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10265786/
https://www.ncbi.nlm.nih.gov/pubmed/37312026
http://dx.doi.org/10.1186/s12880-023-01023-4

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