Search Results - "MAMMOGRAMS"

Combining modified hyper learning binary dragonfly algorithm and deep learning for BI‐RADS classification of breast masses in mammograms.

Authors: Khanna, Priyanka Sahu, Mridu Singh, Bikesh Kumar et al.

Source: Expert Systems. Jun2026, Vol. 43 Issue 6, p1-12. 12p.

Optimized ResNet-50 framework for mammogram-based breast cancer classification: a comparative evaluation with EfficientNet-B0.

Authors: Subali, Muhammad Wisudawati, Lulu Mawaddah Teresa

Source: International Journal of Electrical & Computer Engineering (2088-8708). Jun2026, Vol. 16 Issue 3, p1199-1212. 14p.

Subjects: Mammograms, Convolutional neural networks, Breast cancer, Deep learning, Diagnostic imaging, Computer-aided diagnosis

Lesion-Aware Image Augmentation for Robust Mammogram Classification.

Authors: Khongkraphan, Kittiya Jareanpon, Chatklaw

Source: Applied Sciences (2076-3417); Jun2026, Vol. 16 Issue 11, p5505, 15p

Comparison of High-Risk Breast Cancer Screenings with Concurrent Versus Staggered Breast MRI and Mammogram Schedules.

Authors: Cornell, Lauren Foster Plante, Marie Pai, Tanmayi et al.

Source: Journal of Clinical Medicine. Jun2026, Vol. 15 Issue 11, p4239. 12p.

The Impact of Artificial Intelligence on BI-RADS Classification and Diagnostic Confidence in Mammography Interpretation by Radiology Residents.

Authors: Cîrlig, Ioana-Andreea Olaru, Alexandru-Marian Ene, Mihai-Alexandru et al.

Source: Life (2075-1729). Jun2026, Vol. 16 Issue 6, p1020. 20p.

Cross-Center Vision–Language Transformer for Robust Mammography-Based Breast Cancer Diagnosis.

Authors: Abulfaraj, Anas W.¹ (AUTHOR)

Source: Bioengineering (Basel). Jun2026, Vol. 13 Issue 6, p653. 43p.

Deep convolutional neural networks accurately predict breast cancer using mammograms.

Authors: Hussain, Lal Ansari, Sara Shabir, Mamoona et al.

Source: Waves in Random & Complex Media. Jun2026, Vol. 36 Issue 3, p4512-4535. 24p.

Assessing Multimodality Breast Cancer Screening Strategies for BRCA1/2 Gene Mutation Carriers and Other High-Risk Populations.

Authors: Çağlayan, Çağlar Ayer, Turgay Ekwueme, Donatus U.

Source: INFORMS Journal on Computing; May/Jun2026, Vol. 38 Issue 3, p802-828, 27p

A Cross-Sectional Analysis of Women Attending a Free Screening Mammography Campaign at a University Hospital in Lebanon.

Authors: El Khoury, Tracy Ibrahim, Roy Salameh, Pascale et al.

Source: International Journal of Women's Health. May2026, Vol. 19, p1-12. 12p.

Breast density classification in mammograms using VGG convolutional networks.

Authors: Cruz, Elsy Santos, Lourdes Calvo, Hiram et al.

Source: Journal of Intelligent & Fuzzy Systems. Feb2026, Vol. 50 Issue 2, p611-619. 9p.

Numerical Interpretation of Variation Indices of Tumor Outline Tracking Using Artificial Intelligence Mapping.

Authors: Mortazavy Beni, Hamidreza¹ (AUTHOR) HRM.Beni@iau.ac.ir

Source: Biomedical Engineering & Computational Biology. 4/15/2026, Vol. 17, p1-16. 16p.

Subjects: Cancer diagnosis, Mammograms, Feature extraction, Artificial intelligence, Deep learning, Diagnosis, Machine learning

Meet the American spies who helped mammograms save more lives.

Authors: German, Erik (AUTHOR)

Source: Fortune.com. 2/16/2026, pN.PAG-N.PAG. 1p.

Towards an improved deep learning algorithm-based diagnostic model for the classification of breast cancer.

Authors: Huang, Zhicheng Gupta, Ashish Wagh, Kishor S. et al.

Source: KSII Transactions on Internet & Information Systems; Apr2026, Vol. 20 Issue 4, p1920-1941, 22p

TRANSFER LEARNING-DRIVEN DEEP NEURAL NETWORK FRAMEWORK FOR EARLY AND ACCURATE BREAST CANCER DETECTION.

Authors: D. B., Shanmugam S., Athinarayanan A., Josephine Christilda et al.

Source: Kufa Journal of Engineering; Apr2026, Vol. 17 Issue 2, p628-646, 19p

Energy-Resolved CNR Performance in Dense-Breast and Implant X-Ray Mammography Using a CdTe Photon-Counting Detector: A Monte Carlo Study.

Authors: Roque, Gerardo Pérez-Lara, Maria Laura Cely, Steven et al.

Source: Applied Sciences (2076-3417); Apr2026, Vol. 16 Issue 7, p3550, 21p

MassSeg-Framework: A Breast Mass Detection and Segmentation Framework Based on Deep Learning and an Active Contour Model.

Authors: Zambrano, Camila Pérez-Pérez, Noel Coimbra, Miguel et al.

Source: Life (2075-1729). Apr2026, Vol. 16 Issue 4, p653. 25p.

Disparities in cancer screening and preventive care access among LGBTQ+ populations: A cross-sectional study.

Authors: Pustake, Manas Garikiparthy, Veeravenkata Ganiyani, Mohammed Arfat et al.

Source: Journal of Family Medicine & Primary Care. Apr2026, Vol. 15 Issue 4, p1740-1746. 7p.

Bridging Pixels and Practice: AI-Assisted Mammography as a Next-Generation Diagnostic Strategy for Breast Cancer Screening.

Authors: Galappaththi, Dulanjani De Silva, Malinda Jawed, Muhammad et al.

Source: Diagnostics (2075-4418). Mar2026, Vol. 16 Issue 6, p873. 17p.

PSO-Based Ensemble Learning Enhanced with Explainable Artificial Intelligence for Breast Glandular Dose Estimation in Mammography.

Authors: Ünal, Sevgi Gürfidan, Remzi

Source: Applied Sciences (2076-3417); Mar2026, Vol. 16 Issue 5, p2514, 21p

Beyond mammography: Superior performance of ultrasound in early-onset breast cancer implications for age-specific, density-tailored screening.

Authors: Shaber, Salman Saad Bin Alsahli, Fahad Mohammed Alotaibi, Maher Mohammed et al.

Source: Turkish Journal of Surgery / Bilimsel Tip Yayinevi. Mar2026, Vol. 42 Issue 1, p57-66. 10p.