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Early Breast Cancer Detection Based on Deep Learning: An Ensemble Approach Applied to Mammograms

• Authors : Youness Khourdifi; Alae El Alami; Mounia Zaydi

Subjects: 03 medical and health sciences; convolutional neural networks (CNNs); 0302 clinical medicine

• Source: BioMedInformatics, Vol 4, Iss 4, Pp 2338-2373 (2024)

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Analyzing the breast tissue in mammograms using deep learning

• Authors : Saffari Tabalvandani, Nasibeh; University/Department: Universitat Rovira i Virgili. Departament d'Enginyeria Informàtica i Matemàtiques; ...

Subjects: Aprenentatge profund; Mamografies; Càncer de mama

• Source: TDX (Tesis Doctorals en Xarxa)

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

• Authors : Ahmad, Sultan^1,2 (AUTHOR) ; Neal Joshua, Eali Stephen³ (AUTHOR); Rao, Nakka Thirupathi⁴ (AUTHOR)

• Source: Scientific Reports. 10/23/2025, Vol. 15 Issue 1, p1-23. 23p.

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An uncertainty estimator method based on the application of feature density to classify mammograms for breast cancer detection.

• Authors : Fuentes-Fino, Ricardo¹ (AUTHOR); Calderón-Ramírez, Saúl² (AUTHOR); Domínguez, Enrique^1,3 (AUTHOR)

• Source: Neural Computing & Applications. Oct2023, Vol. 35 Issue 30, p22151-22161. 11p.

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A YOLO-based AI system for classifying calcifications on spot magnification mammograms.

• Authors : Chen, Jian-Ling^1,2 (AUTHOR); Cheng, Lan-Hsin³ (AUTHOR); Wang, Jane^2,4,5 (AUTHOR)

• Source: BioMedical Engineering OnLine. 5/27/2023, Vol. 22 Issue 1, p1-15. 15p.

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A shortcut weighted fusion pyramid network for microcalcification detection in breast mammograms.

• Authors : Zhao, Huairui¹ (AUTHOR); Hua, Jia² (AUTHOR); Geng, Xiaochuan² (AUTHOR)

• Source: Technology & Health Care. 2023, Vol. 31 Issue 3, p841-853. 13p.

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Deep feature selection using local search embedded social ski-driver optimization algorithm for breast cancer detection in mammograms.

• Authors : Pramanik, Payel¹ (AUTHOR); Mukhopadhyay, Souradeep¹ (AUTHOR); Mirjalili, Seyedali^2,3,4 (AUTHOR)

• Source: Neural Computing & Applications. Mar2023, Vol. 35 Issue 7, p5479-5499. 21p.

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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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Development of an Artificial Intelligence-Based Breast Cancer Detection Model by Combining Mammograms and Medical Health Records.

• Authors : Trang, Nguyen Thi Hoang¹ (AUTHOR); Long, Khuong Quynh² (AUTHOR); An, Pham Le^3,4 (AUTHOR)

• Source: Diagnostics (2075-4418). Feb2023, Vol. 13 Issue 3, p346. 18p.

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Evaluation of deep learning-based artificial intelligence techniques for breast cancer detection on mammograms: Results from a retrospective study using a BreastScreen Victoria dataset.

• Authors : Frazer HM; St Vincent's BreastScreen, St Vincent's Hospital Melbourne, Melbourne, Victoria, Australia.; Qin AK

Subjects: Breast Neoplasms*/Breast Neoplasms*/Breast Neoplasms*/diagnostic imaging ; Deep Learning*; Female

• Source: Journal of medical imaging and radiation oncology [J Med Imaging Radiat Oncol] 2021 Aug; Vol. 65 (5), pp. 529-537. Date of Electronic Publication: 2021 Jul 01.Publisher: Wiley-Blackwell Pub. Asia Country of Publication: Australia NLM ID: 101469340 Publication Model: Print-Electronic Cited Medium: Internet

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