Using Radiomics-Based Machine Learning to Create Targeted Test Sets to Improve Specific Mammography Reader Cohort Performance: A Feasibility Study

Mammography interpretation is challenging with high error rates. This study aims to reduce the errors in mammography reading by mapping diagnostic errors against global mammographic characteristics using a radiomics-based machine learning approach. A total of 36 radiologists from cohort A (n = 20) a...

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Detalles Bibliográficos
Autores principales: Tao, Xuetong, Gandomkar, Ziba, Li, Tong, Brennan, Patrick C., Reed, Warren
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10300999/
https://www.ncbi.nlm.nih.gov/pubmed/37373877
http://dx.doi.org/10.3390/jpm13060888

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10300999/
https://www.ncbi.nlm.nih.gov/pubmed/37373877
http://dx.doi.org/10.3390/jpm13060888

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