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Enhanced Interpretability in Breast Cancer Detection: Combining Grad‐ CAM With Selective Layer Freezing in Deep Learning

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1 of the 21 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1007/s11042-024-20011-6 (notice 2026-04-16).

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What this work says

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

inferredcites →https://doi.org/10.1002/ima.70008openalex-snapshot

YOLOv8 Outperforms Traditional CNN Models in Mammography Classification: Insights From a Multi‐Institutional Dataset

inferredcites →https://doi.org/10.1007/s11042-023-17776-7openalex-snapshot

Attention guided grad-CAM : an improved explainable artificial intelligence model for infrared breast cancer detection

inferredcites →https://doi.org/10.1007/s11042-024-20011-6openalex-snapshot

RETRACTED ARTICLE: Deep learning approaches to detect breast cancer: a comprehensive review

inferredcites →https://doi.org/10.1016/j.artmed.2022.102419openalex-snapshot

Breast cancer detection and classification in mammogram using a three-stage deep learning framework based on PAA algorithm

inferredcites →https://doi.org/10.1016/j.irbm.2020.12.004openalex-snapshot

Automatic Detection and Classification of Mammograms Using Improved Extreme Learning Machine with Deep Learning

inferredcites →https://doi.org/10.1038/s41598-023-29875-4openalex-snapshot

Efficient breast cancer mammograms diagnosis using three deep neural networks and term variance

inferredcites →https://doi.org/10.1109/access.2024.3520608openalex-snapshot

Breast Cancer Classification With Enhanced Interpretability: DALAResNet50 and DT Grad-CAM

inferredcites →https://doi.org/10.1109/icicos62600.2024openalex-snapshot

2024 7th International Conference on Informatics and Computational Sciences (ICICoS)

inferredcites →https://doi.org/10.1109/icitiit61487.2024.10580410openalex-snapshot

Breast Cancer Detection Using Watershed and Back Propagation Algorithm

inferredcites →https://doi.org/10.1109/inmic64792.2024.11004362openalex-snapshot

Enhancing Breast Cancer Diagnosis in Mammography: Evaluation and Integration of Convolutional Neural Networks and Explainable AI

inferredcites →https://doi.org/10.1109/inocon60754.2024.10512277openalex-snapshot

Breast Cancer Prediction by Ensembling Machine Learning Algorithms and Explainable AI

inferredcites →https://doi.org/10.1145/3608164.3608167openalex-snapshot

Patch-based deep learning models for breast mammographic mass classification

inferredcites →https://doi.org/10.1259/bjr.20211033openalex-snapshot

Understanding breast cancer as a global health concern

inferredcites →https://doi.org/10.22214/ijraset.2024.60942openalex-snapshot

Prediction of Abnormal Growth of Breast Cancer Cell Using Support Vector Machine

inferredcites →https://doi.org/10.25163/angiotherapy.879806openalex-snapshot

Artificial Intelligence in Breast Cancer Screening in Inducing Diagnostic Accuracy with Early Detection

inferredcites →https://doi.org/10.3390/app112311398openalex-snapshot

Classification of Breast Cancer in Mammograms with Deep Learning Adding a Fifth Class

inferredcites →https://doi.org/10.3390/app13074272openalex-snapshot

Applying Deep Learning Methods for Mammography Analysis and Breast Cancer Detection

inferredcites →https://doi.org/10.3390/diagnostics13030348openalex-snapshot

A Novel Medical Image Enhancement Algorithm for Breast Cancer Detection on Mammography Images Using Machine Learning

inferredcites →https://doi.org/10.3390/life14111451openalex-snapshot

Artificial Intelligence in Breast Cancer Diagnosis and Treatment: Advances in Imaging, Pathology, and Personalized Care

inferredcites →https://doi.org/10.3390/s21175813openalex-snapshot

Detection of COVID-19 Using Transfer Learning and Grad-CAM Visualization on Indigenously Collected X-ray Dataset

inferredcites →https://doi.org/10.4048/jbc.2023.26.e45openalex-snapshot

Artificial Intelligence in Breast Cancer Diagnosis and Personalized Medicine

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.70299openalex-snapshot

Robust and Multicenter Detection of Breast Malignancies Using Vision Transformers in Digital Breast Tomosynthesis Imaging

inferred← citeshttps://doi.org/10.1002/widm.70075openalex-snapshot

Interpretable Machine Learning: A Comprehensive Review of Foundations, Methods, and the Path Forward

inferred← citeshttps://doi.org/10.1007/s00234-026-04053-1openalex-snapshot

Integrated CT–PET radiogenomics and graph-based multi-task learning for preoperative prediction of key glioma molecular markers

inferred← citeshttps://doi.org/10.1007/s00261-026-05536-8openalex-snapshot

Clinically interpretable nomogram incorporating radiomics and deep learning feature fusion from abdominal CT for preclinical type 2 diabetes

inferred← citeshttps://doi.org/10.1007/s12672-026-04823-6openalex-snapshot

Pancreatic multi structure segmentation on CT using transformer and deep learning approaches

inferred← citeshttps://doi.org/10.1016/j.cmpbup.2026.100251openalex-snapshot

Deep transfer learning for breast cancer classification in mammography: A systematic review

inferred← citeshttps://doi.org/10.1016/j.ejmp.2026.105806openalex-snapshot

A novel multi-task deep learning framework for classification and detection of intracranial structures in first-trimester fetal ultrasound images

inferred← citeshttps://doi.org/10.1016/j.jvoice.2025.09.033openalex-snapshot

A Novel Machine Learning-Driven Voice and Clinical Biomarkers Framework for Robust Prediction of Type 2 Diabetes Mellitus

inferred← citeshttps://doi.org/10.1016/j.pdpdt.2026.105455openalex-snapshot

Multi-task transformer framework and radiomic signatures for multi-lesion segmentation, detection, and grading in diabetic retinopathy

inferred← citeshttps://doi.org/10.1109/iceconf65644.2025.11379493openalex-snapshot

AECNN: A Dual-Stage Deep Learning Framework for Accurate and Efficient Ultrasound-Based Breast Cancer Detection

inferred← citeshttps://doi.org/10.1111/echo.70527openalex-snapshot

Multi‐Center Adversarial Bi‐Phase Cross‐Attention Network for Right Ventricular Segmentation and Functional Classification in Echocardiography

inferred← citeshttps://doi.org/10.1140/epjp/s13360-026-08320-1openalex-snapshot

A lightweight web-based breast cancer classification and interpretable severity assessment using 3D Inception convolutional squeeze-excitation selective subject encoder

inferred← citeshttps://doi.org/10.1186/s12891-026-10043-4openalex-snapshot

Clinically integrated multi-modal transformer framework with cross-modal gated fusion and clinical nomogram for automated Kellgren-Lawrence grading of knee osteoarthritis on x-ray images

inferred← citeshttps://doi.org/10.1186/s13000-026-01754-2openalex-snapshot

Integrating histopathology and immune marker analysis for machine learning-based colorectal cancer prognostics

inferred← citeshttps://doi.org/10.1186/s13000-026-01769-9openalex-snapshot

A novel multimodal framework integrating pathomics, deep learning, and machine learning for breast cancer histological grades classification

inferred← citeshttps://doi.org/10.1186/s40001-025-03204-zopenalex-snapshot

Novel multi-task learning for Alzheimer’s stage classification using hippocampal MRI segmentation, feature fusion, and nomogram modeling

inferred← citeshttps://doi.org/10.1186/s40001-026-04766-2openalex-snapshot

An interpretable AI multimodal framework for predicting anesthesia-related hemodynamic instability: radiomics and deep feature extraction from preoperative contrast-enhanced CT combined with intraoperative clinical vital signs

inferred← citeshttps://doi.org/10.1186/s40537-025-01315-2openalex-snapshot

Natural language processing for extracting consumer sentiment dynamics through multimodal social media analysis to predict microeconomic consumption pattern shifts

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