Machine learning based Breast Cancer screening: trends, challenges, and opportunities
Author:
Affiliation:
1. Mohammed VI Polytechnic University, Benguerir, Morocco
2. Software Project Management Research Team, ENSIAS, Mohammed V University, Rabat, Morocco
Publisher
Informa UK Limited
Subject
Computer Science Applications,Radiology, Nuclear Medicine and imaging,Biomedical Engineering,Computational Mechanics
Link
https://www.tandfonline.com/doi/pdf/10.1080/21681163.2023.2172615
Reference105 articles.
1. Deep Learning to Distinguish Recalled but Benign Mammography Images in Breast Cancer Screening
2. Thermography Based Breast Cancer Detection Using Texture Features and Support Vector Machine
3. Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent
4. Automatic mass detection in mammograms using deep convolutional neural networks
5. Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms
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1. Evaluating and comparing bagging and boosting of hybrid learning for breast cancer screening;Scientific African;2024-03
2. Application of neuro-fuzzy ensembles across domains: A systematic review of the two last decades (2000–2022);Engineering Applications of Artificial Intelligence;2023-09
3. Estimation of Impedance Features and Classification of Carcinoma Breast Cancer Using Optimization Techniques;BioMedInformatics;2023-05-06
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