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Deep learning and optimization algorithms for automatic breast cancer detection

https://doi.org/10.1002/ima.22400
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/ima.22484openalex-snapshot
Detection and classification of breast cancer from digital mammograms using hybrid extreme learning machine classifier
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Real‐time automated segmentation of breast lesions using CNN‐based deep learning paradigm: Investigation on mammogram and ultrasound
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Classifications of benign and malignant mammogram images using Gabor‐modified CNN architecture
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Dual-Feature CNN-SVM Method for Breast Mass Tissue Abnormality Classification on Digital Mammography Images Adapted to Breast Density
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Feature Selection and Diagnosis Performance Evaluation of Breast Cancer
inferred← citeshttps://doi.org/10.1007/978-981-19-3089-8_58openalex-snapshot
Deep Learning Based Framework for Breast Cancer Mammography Classification Using Resnet50
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MAMMO-Net: An Approach for Classification of Breast Cancer using CNN with Gabor Filter in Mammographic Images
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TFEA-Net: Triplet Feature Enhancement Attention Network for Breast Cancer Classification
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Breast lesions classifications of mammographic images using a deep convolutional neural network-based approach
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An optimized model based on adaptive convolutional neural network and grey wolf algorithm for breast cancer diagnosis
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HGMMEM Algorithm with Optimized DCNN Classification for Breast Cancer Image Screening and Detection
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A Transfer Learning-Based Deep Learning Model for Automated Breast Cancer Identification in Mammograms
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A Transfer Learning-Based Deep Learning Model for Automated Breast Cancer Identification in Mammograms
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A Transfer Learning-Based Deep Learning Model for Automated Breast Cancer Identification in Mammograms
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A Transfer Learning-Based Deep Learning Model for Automated Breast Cancer Identification in Mammograms
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A Systematic Literature Review on Mammography: Deep Learning in Redefining Breast Cancer Diagnosis for the Asian Perspective
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A Novel Transfer-Learning Model for Automatic Detection and Classification of Breast Cancer Based Deep CNN
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A Comprehensive Bibliometric Analysis of Deep Learning Techniques for Breast Cancer Segmentation: Trends and Topic Exploration (2019-2023)
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Automatic Mammogram image Breast Abnormality Detection and localization based on the combination of k-means and Genetic algorithms methods
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Breast cancer diagnosis using Orca predation optimization algorithm
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RETRACTED: Classification of mammogram breast cancer using customized deep learning model
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Classification of Multi-view Digital Mammogram Images Using SMO-WkNN
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Review of Artificial Intelligence Techniques for Breast Cancer Detection with Different Modalities: Mammography, Ultrasound, and Thermography Images
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An Automated In-Depth Feature Learning Algorithm for Breast Abnormality Prognosis and Robust Characterization from Mammography Images Using Deep Transfer Learning
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Tensor-Based Learning for Detecting Abnormalities on Digital Mammograms
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Multi-Scale Vision Transformer with Optimized Feature Fusion for Mammographic Breast Cancer Classification
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An IoT-Based Framework and Ensemble Optimized Deep Maxout Network Model for Breast Cancer Classification
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BAS-SegNet: A Boundary-Aware Sobel-Enhanced Deep Learning Framework for Breast Cancer and Skin Cancer Segmentation
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Breast Cancer Detection and Classification Using Hybrid Feature Selection and DenseXtNet Approach
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Attention-Based Ensemble Network for Effective Breast Cancer Classification over Benchmarks
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Estimation of Breast Cancer with a Combined Feature Selection Algorithm
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Generic hybrid model for breast cancer mammography image classification using EfficientNetB2
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