نتائج البحث

Calcifications of the breast.

• Authors : Crowder, Charlotte, MPH, ELS

Subjects: Calcium in the body; Breast abnormalities; Calcifications of the breast

• Source: Salem Health: Cancer (Online Edition), 2025. 2p.

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HyFusion-X: hybrid deep and traditional feature fusion with ensemble classifiers for breast cancer detection using mammogram and ultrasound images.

• Authors : Shaukat, Anum¹ (AUTHOR); Farhan, Saima¹ (AUTHOR); Javed, Rabia¹ (AUTHOR)

Subjects: *BREAST cancer; *MAMMOGRAMS; *DETECTION algorithms

• Source: Scientific Reports. 11/3/2025, Vol. 15 Issue 1, p1-29. 29p.

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ASG-MammoNet: an attention-guided framework for streamlined and interpretable breast cancer classification from mammograms

• Authors : Hosameldin O. A. Ahmed; Asoke K. Nandi

Subjects: breast cancer diagnosis; computer-aided diagnosis; deep learning

• Source: Frontiers in Signal Processing, Vol 5 (2025)

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BREAST TUMOUR DETECTION AND CLASSIFICATION: A SURVEY.

• Authors : Sharma, Sangeeta¹; Shrivastava, Megha²; Gupta, Ved Kumar³

• Source: International Journal of Zoology & Applied Biosciences. 2025, Vol. 10 Issue 6, p211-228. 18p.

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Implementation and initial outcomes of a breast cancer screening program in remote areas: a case study in the western Amazon, Brazil

• Authors : Ana Maria Negreiros; Thiago Silva; Anderson Teixeira

Subjects: Brazil; breast neoplasms; developing countries

• Source: Rural and Remote Health, Vol 25 (2025)

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Optimising breast cancer screening in national mammography screening centres: challenges and insights on implementing additional ultrasound for women with dense breast tissue — a qualitative study.

• Authors : Elsner, Susanne A.¹ (AUTHOR) ; Haußmann, Eva² (AUTHOR); Grieger, Paula¹ (AUTHOR)

• Source: BMC Cancer. 10/31/2025, Vol. 25 Issue 1, p1-10. 10p.

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Breast Cancer VLMs: Clinically Practical Vision-Language Train-Inference Models

• Authors : Zheng, Shunjie-Fabian; Lee, Hyeonjun; Kooi, Thijs

Subjects: Computer Vision and Pattern Recognition; Machine Learning

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Deep learning-based bacterial foraging optimization algorithm to improve digital mammography-based breast cancer detection.

• Authors : Banumathy, D.¹ (AUTHOR) ; Karthikeyan, D.² (AUTHOR) ; Mohanraj, G.² (AUTHOR)

• Source: Scientific Reports. 10/29/2025, Vol. 15 Issue 1, p1-18. 18p.

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Mammography and Breast Arterial Calcification: An Information-Sharing Trial

• Authors : National Cancer Institute (NCI); Guy Montgomery, Professor, Department of Population Health Science and Policy

• Source: Enhancing the Public Health Benefits of Mammography Screening by Informing Women of Both Breast Cancer and Breast Arterial Calcification Results: A Randomized Trial to Promote Cardiovascular Health

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A multi stage deep learning model for accurate segmentation and classification of breast lesions in mammography.

• Authors : Ahmad S; Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Alkharj, 11942, Saudi Arabia. .; School of Computer Science and Engineering, Lovely Professional University, Phagwara, 144411, Punjab, India. .

Subjects: Deep Learning* ; Mammography*/Mammography*/Mammography*/methods ; Breast Neoplasms*/Breast Neoplasms*/Breast Neoplasms*/diagnostic imaging

• Source: Scientific reports [Sci Rep] 2025 Oct 23; Vol. 15 (1), pp. 37103. Date of Electronic Publication: 2025 Oct 23.Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN:

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