Article

FTAD-Net: Federated Transfer-Adversarial Learning for Robust Breast Cancer Detection

2026-04-14

Abstract excerpt

<title>Abstract</title> <p>Breast cancer remains the second leading cause of cancer-related mortality among women worldwide, making early and accurate diagnosis pivotal for improving patient survival rates. Although deep learning (DL) models have demonstrated remarkable potential in automated breast cancer detection, their large-scale clinical deployment is hindered by challenges such as limited annotated data, i...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 9fa52e29-82c6-50b4-add2-bc797b4cecd3
DOI: 10.21203/rs.3.rs-9192952/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

FTAD-Net: Federated Transfer-Adversarial Learning for Robust Breast Cancer DetectionDOI 10.21203/rs.3.rs-9192952/v1Read

Federated Learning-Driven Collaborative Diagnostic System for Metastatic Breast CancerSemantic proximity Read

Histo-Fusion: A novel domain specific learning to identify Invasive Ductal Carcinoma (IDC) from Histopathological ImagesSemantic proximity Read

Flexible and Scalable Federated Learning with Deep Feature Prompts for Digital PathologySemantic proximity Read

Federated deep learning enables cancer subtyping by proteomicsSemantic proximity Read

Federated Learning for Multi-Center Imaging Diagnostics: A Study in Cardiovascular DiseaseSemantic proximity Read

not-yet-known not-yet-known not-yet-known unknown MammoDenseInvoNet: Involution Based DenseNet Architecture for Classification of Breast Mass From Cross National DatasetsSemantic proximity Read

Learning Interpretable Microscopic Features of Tumor by Multi-task Adversarial CNNs Improves GeneralizationSemantic proximity Read

Enhancing Breast Cancer Detection through Advanced Data Augmentation and Feature Engineering with Radiomics and Transfer LearningSemantic proximity Read

Federated CT Foundation Models for Multi-Center Detection of Lymph Node Metastasis in Pancreatic CancerSemantic proximity Read

Cross-institutional HER2 assessment via a computer-aided system using federated learning and stain composition augmentationSemantic proximity Read

Developing Deep Learning Models for Classifying Medical Imaging DataSemantic proximity Read

Advancing oncology with federated learning: transcending boundaries in breast, lung, and prostate cancer. A systematic reviewSemantic proximity Read