ReviewComputational and mathematical methods in medicine2017
Involvement of Machine Learning for Breast Cancer Image Classification: A Survey.
Review in Computational and mathematical methods in medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Experimental and Monte Carlo Insights into the Biofilm Control ofNanomaterials (Basel, Switzerland) · 2026Article
- Bibliometric analysis of research on artificial İntelligence applications in breast cancer diagnosis.Technology and health care : official journal of the European Society for Engineering and Medicine · 2026Article
- Breast lesion classification via colorized mammograms and transfer learning in a novel CAD framework.Scientific reports · 2025Article
- Comprehensive study of semi-supervised learning for DNA methylation-based supervised classification of central nervous system tumors.BMC bioinformatics · 2022Article
- Machine Learning Approach to Quadratic Programming-Based Microwave Imaging for Breast Cancer Detection.Sensors (Basel, Switzerland) · 2022Article
- Deep Learning on Histopathology Images for Breast Cancer Classification: A Bibliometric Analysis.Healthcare (Basel, Switzerland) · 2021Article
- Review
- Breast histopathological image analysis using image processing techniques for diagnostic puposes: A methodological review.Journal of medical systems · 2021Review
- Automatic breast tissue segmentation in MRIs with morphology snake and deep denoiser training via extended Stein's unbiased risk estimator.Health information science and systems · 2021Article
- Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey.Life (Basel, Switzerland) · 2021Review
- Review
- Reviewing Machine Learning and Image Processing Based Decision-Making Systems for Breast Cancer Imaging.Journal of medical systems · 2021Article
- Dynamic Learning Rate in Deep CNN Model for Metastasis Detection and Classification of Histopathology Images.Computational and mathematical methods in medicine · 2021Article
- Convolutional neural network for automated mass segmentation in mammography.BMC bioinformatics · 2020Article
- Spatially localized sparse representations for breast lesion characterization.Computers in biology and medicine · 2020Article
- A Deep Learning Approach for Missing Data Imputation of Rating Scales Assessing Attention-Deficit Hyperactivity Disorder.Frontiers in psychiatry · 2020Article
- Analysis of theInternational journal of molecular sciences · 2019Article
- Application of Radiomics and Decision Support Systems for Breast MR Differential Diagnosis.Computational and mathematical methods in medicine · 2018Review
- A Semi-Supervised Method for Tumor Segmentation in Mammogram Images.Journal of medical signals and sensorsArticle
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer is one of the largest causes of women's death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors' and physicians' time. Despite the various publications on breast image classification, very few review papers are available which provide a detailed description of breast cancer image classification techniques, feature extraction and selection procedures, classification measuring parameterizations, and image classification findings. We have put a special emphasis on the Convolutional Neural Network (CNN) method for breast image classification. Along with the CNN method we have also described the involvement of the conventional Neural Network (NN), Logic Based classifiers such as the Random Forest (RF) algorithm, Support Vector Machines (SVM), Bayesian methods, and a few of the semisupervised and unsupervised methods which have been used for breast image classification.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.