Deep learning approaches for detection, classification, and localization of breast cancer using microscopic images: A review and bibliometric analysis DOI
Sonam Tyagi, Subodh Srivastava, Bikash Chandra Sahana

et al.

Research on Biomedical Engineering, Journal Year: 2024, Volume and Issue: 41(1)

Published: Dec. 27, 2024

Language: Английский

Hybrid Feature Extraction for Breast Cancer Classification Using the Ensemble Residual VGG16 Deep Learning Model DOI
Zhenfei Wang,

Muhammad Mumtaz Ali,

Kashif Iqbal Sahibzada

et al.

Current Bioinformatics, Journal Year: 2024, Volume and Issue: 20(2), P. 149 - 163

Published: Oct. 30, 2024

Introduction: Breast Cancer (BC) is a significant cause of high mortality amongst women globally and probably will remain disease posing challenges about its detectability. Advancements in medical imaging technology have improved the accuracy efficiency breast cancer classification. However, tumor features' complexity data variability still pose challenges. Method: This study proposes Ensemble Residual-VGG-16 model as novel combination Deep Residual Network (DRN) VGG-16 architecture. purposely engineered with maximal precision for task diagnosis based on mammography images. We assessed performance by accuracy, recall, precision, F1-Score. All these metrics indicated this model. The diagnostic residual-VGG16 performed exceptionally well an 99.6%, 99.4%, recall 99.7%, F1 score 98.6%, Mean Intersection over Union (MIoU) 99.8% MIAS datasets. Result: Similarly, INBreast dataset achieved 93.8%, 94.2%, 94.5%, F1-score 93.4%. Conclusion: proposed advancement diagnosis, potential automated grading.

Language: Английский

Citations

1
IoT based healthcare system using Fractional dung beetle optimization enabled deep learning for breast cancer classification DOI
V. Vasudha Rani,

G. Vasavi,

P. Mano Paul

et al.

Computational Biology and Chemistry, Journal Year: 2024, Volume and Issue: 114, P. 108277 - 108277

Published: Nov. 10, 2024

Language: Английский

Citations

1
Mammography Breast Cancer Classification Using Vision Transformers DOI
Mouhamed Laid Abimouloud, Khaled Bensid, Mohamed Elleuch

et al.

Lecture notes in networks and systems, Journal Year: 2024, Volume and Issue: unknown, P. 452 - 461

Published: Jan. 1, 2024

Language: Английский

Citations

1
Deep learning for breast cancer diagnosis from histopathological images: classification and gene expression: review DOI

Oumeima Thaalbi,

Moulay A. Akhloufi

Network Modeling Analysis in Health Informatics and Bioinformatics, Journal Year: 2024, Volume and Issue: 13(1)

Published: Sept. 26, 2024

Language: Английский

Citations

1
Deep learning approaches for detection, classification, and localization of breast cancer using microscopic images: A review and bibliometric analysis DOI
Sonam Tyagi, Subodh Srivastava, Bikash Chandra Sahana

et al.

Research on Biomedical Engineering, Journal Year: 2024, Volume and Issue: 41(1)

Published: Dec. 27, 2024

Language: Английский

Citations

0