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Cancer
February 2025
General Medicine Service, VA Puget Sound Health Care System, Seattle, Washington, USA.
Background: Breast cancer screening (BCS) inequities are evident at national and local levels, and many health systems want to address these inequities, but may lack data about contributing factors. The objective of this study was to inform health system interventions through an exploratory analysis of potential multilevel contributors to BCS inequities using health system data.
Methods: The authors conducted a cross-sectional analysis within a large academic health system including 19,774 individuals who identified as Black (n = 1445) or White (n = 18,329) race and were eligible for BCS.
BMC Res Notes
January 2025
Department of Surgery, Department of Clinical Sciences, Division of Surgery, Skåne University Hospital, Lund University, Lund, Sweden.
Objectives: Positive resection margins after breast-conserving surgery (BCS) most often demands a repeat surgery. To preoperatively identify patients at risk of positive margins, a multivariable model has been developed that predicts positive margins after BCS with a high accuracy. This study aimed to externally validate this prediction model to explore its generalizability and assess if additional preoperatively available variables can further improve its predictive accuracy.
View Article and Find Full Text PDFNihon Hoshasen Gijutsu Gakkai Zasshi
January 2025
Department of Risk Analysis and Biodosimetry, Institute of Radiation Emergency Medicine, Hirosaki University.
Purpose: Hereditary breast and ovarian cancers (HBOC) carry a high risk of breast cancer, and detailed screening with contrast-enhanced breast MRI (breast MRI surveillance) is recommended. With the increase in the number of individuals diagnosed with HBOC, the demand for breast MRI surveillance is also rising. However, the current system is inadequate, with factors such as lack of knowledge and indifference among healthcare professionals, and insufficient understanding of breast MRI surveillance being cited.
View Article and Find Full Text PDFSci Rep
January 2025
College of Information Science and Technology, Hainan Normal University, Haikou, 571158, China.
Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for reducing mortality rates and ensuring timely treatment. Computer-aided diagnosis systems provide automated mammography image processing, interpretation, and grading. However, since the currently existing methods suffer from such issues as overfitting, lack of adaptability, and dependence on massive annotated datasets, the present work introduces a hybrid approach to enhance breast cancer classification accuracy.
View Article and Find Full Text PDFCancers (Basel)
January 2025
Mitos Medical Technologies, ITU Ayazaga Ari 1, Maslak, 34469 Istanbul, Turkey.
Background/objectives: Breast cancer is a significant global health concern, and early detection is crucial for improving patient outcomes. Mammography is widely used but has limitations, particularly for younger women with denser breasts. These include reduced sensitivity, false positives, and radiation risks.
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