Generalisable deep learning method for mammographic density prediction across imaging techniques and self-reported race

• Published in: Communications medicine Vol. 4; no. 1; pp. 21 - 8
• Main Authors: Khara, Galvin, Trivedi, Hari, Newell, Mary S., Patel, Ravi, Rijken, Tobias, Kecskemethy, Peter, Glocker, Ben
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 19.02.2024; Springer Nature B.V; Nature Portfolio
• Subjects: 59; 692/4028/67/1347; 692/4028/67/2322; 692/700/1421; 692/700/478/2772; Automation; Breast cancer; Datasets; Deep learning; Health risk assessment; Machine learning; Mammography; Medical imaging; Medical technology; Medicine; Medicine & Public Health; Performance evaluation; Race; Racial differences; Reproducibility; Self report

Background Breast density is an important risk factor for breast cancer complemented by a higher risk of cancers being missed during screening of dense breasts due to reduced sensitivity of mammography. Automated, deep learning-based prediction of breast density could provide subject-specific risk a...