Deep learning prediction of mammographic breast density using screening data

Deep learning prediction of mammographic breast density using screening data

Abstract This study investigated a series of deep learning (DL) models for the objective assessment of four categories of mammographic breast density (e.g., fatty, scattered, heterogeneously dense, and extremely dense). A retrospective analysis was conducted using data collected from Taizhou Cancer...

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Bibliographic Details
Main Authors: Chen Chen, Enyu Wang, Vicky Yang Wang, Xiayi Chen, Bojian Feng, Ruxuan Yan, Lingying Zhu, Dong Xu
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Deep learning
Mammography
Automated breast density quantification
Breast cancer risk
Online Access:https://doi.org/10.1038/s41598-025-95275-5
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https://doi.org/10.1038/s41598-025-95275-5

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