Reliable Breast Cancer Molecular Subtype Prediction based on uncertainty-aware Bayesian Deep Learning by Mammography
Fuente:
arXiv
Saved in:
| Main Authors: | Chegini, Mohaddeseh, Mahloojifar, Ali |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
BI-RADS prediction of mammographic masses using uncertainty information extracted from a Bayesian Deep Learning model
by: Chegini, Mohaddeseh, et al.
Published: (2025)
by: Chegini, Mohaddeseh, et al.
Published: (2025)
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification
by: Chegini, Mohaddeseh, et al.
Published: (2025)
by: Chegini, Mohaddeseh, et al.
Published: (2025)
Modifying the U-Net's Encoder-Decoder Architecture for Segmentation of Tumors in Breast Ultrasound Images
by: Derakhshandeh, Sina, et al.
Published: (2024)
by: Derakhshandeh, Sina, et al.
Published: (2024)
Spatial Multi-Task Learning for Breast Cancer Molecular Subtype Prediction from Single-Phase DCE-MRI
by: Zeng, Sen, et al.
Published: (2026)
by: Zeng, Sen, et al.
Published: (2026)
MV-MLM: Bridging Multi-View Mammography and Language for Breast Cancer Diagnosis and Risk Prediction
by: Zheng, Shunjie-Fabian, et al.
Published: (2025)
by: Zheng, Shunjie-Fabian, et al.
Published: (2025)
Adaptive Deep Learning for Breast Cancer Subtype Prediction Via Misprediction Risk Analysis
by: Sheeraz, Gul, et al.
Published: (2025)
by: Sheeraz, Gul, et al.
Published: (2025)
Scalable and Loosely-Coupled Multimodal Deep Learning for Breast Cancer Subtyping
by: Amer, Mohammed, et al.
Published: (2025)
by: Amer, Mohammed, et al.
Published: (2025)
Transformer-Based Explainable Deep Learning for Breast Cancer Detection in Mammography: The MammoFormer Framework
by: Peter, Ojonugwa Oluwafemi Ejiga, et al.
Published: (2025)
by: Peter, Ojonugwa Oluwafemi Ejiga, et al.
Published: (2025)
Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
by: Thrun, Solveig, et al.
Published: (2025)
by: Thrun, Solveig, et al.
Published: (2025)
Attention-Enhanced Deep Learning Ensemble for Breast Density Classification in Mammography
by: Sharifian, Peyman, et al.
Published: (2025)
by: Sharifian, Peyman, et al.
Published: (2025)
Bias and Generalizability of Foundation Models across Datasets in Breast Mammography
by: Germani, Elodie, et al.
Published: (2025)
by: Germani, Elodie, et al.
Published: (2025)
Multimodal Deep Learning for Subtype Classification in Breast Cancer Using Histopathological Images and Gene Expression Data
by: Shandiz, Amin Honarmandi
Published: (2025)
by: Shandiz, Amin Honarmandi
Published: (2025)
Lesion-Aware Generative Artificial Intelligence for Virtual Contrast-Enhanced Mammography in Breast Cancer
by: Rofena, Aurora, et al.
Published: (2025)
by: Rofena, Aurora, et al.
Published: (2025)
OncoVision: Integrating Mammography and Clinical Data through Attention-Driven Multimodal AI for Enhanced Breast Cancer Diagnosis
by: Ahmed, Istiak, et al.
Published: (2025)
by: Ahmed, Istiak, et al.
Published: (2025)
Deep Transfer Learning for Breast Cancer Classification
by: Djagba, Prudence, et al.
Published: (2024)
by: Djagba, Prudence, et al.
Published: (2024)
Multimodal Sheaf-based Network for Glioblastoma Molecular Subtype Prediction
by: Idrissova, Shekhnaz, et al.
Published: (2025)
by: Idrissova, Shekhnaz, et al.
Published: (2025)
Deep Pathomic Learning Defines Prognostic Subtypes and Molecular Drivers in Colorectal Cancer
by: Wang, Zisong, et al.
Published: (2025)
by: Wang, Zisong, et al.
Published: (2025)
Deep Learning-Based Breast Cancer Detection in Mammography: A Multi-Center Validation Study in Thai Population
by: Chamveha, Isarun, et al.
Published: (2025)
by: Chamveha, Isarun, et al.
Published: (2025)
Visualizing the Invisible: Enhancing Radiologist Performance in Breast Mammography via Task-Driven Chromatic Encoding
by: Ye, Hui, et al.
Published: (2026)
by: Ye, Hui, et al.
Published: (2026)
Subtyping Breast Lesions via Generative Augmentation based Long-tailed Recognition in Ultrasound
by: Chen, Shijing, et al.
Published: (2025)
by: Chen, Shijing, et al.
Published: (2025)
Prototype-based Interpretable Breast Cancer Prediction Models: Analysis and Challenges
by: Pathak, Shreyasi, et al.
Published: (2024)
by: Pathak, Shreyasi, et al.
Published: (2024)
Exploring the Interplay Between Colorectal Cancer Subtypes Genomic Variants and Cellular Morphology: A Deep-Learning Approach
by: Hezi, Hadar, et al.
Published: (2023)
by: Hezi, Hadar, et al.
Published: (2023)
Cross-Attention Multimodal Fusion for Breast Cancer Diagnosis: Integrating Mammography and Clinical Data with Explainability
by: Nantogmah, Muhaisin Tiyumba, et al.
Published: (2025)
by: Nantogmah, Muhaisin Tiyumba, et al.
Published: (2025)
Temporal Representation Learning of Phenotype Trajectories for pCR Prediction in Breast Cancer
by: Janíčková, Ivana, et al.
Published: (2025)
by: Janíčková, Ivana, et al.
Published: (2025)
Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning
by: Akbar, Abdul Rehman, et al.
Published: (2026)
by: Akbar, Abdul Rehman, et al.
Published: (2026)
FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography
by: Yang, Julia, et al.
Published: (2024)
by: Yang, Julia, et al.
Published: (2024)
Evaluating Deep Learning Models for Breast Cancer Classification: A Comparative Study
by: Eskandari, Sania, et al.
Published: (2024)
by: Eskandari, Sania, et al.
Published: (2024)
Morpho-Genomic Deep Learning for Ovarian Cancer Subtype and Gene Mutation Prediction from Histopathology
by: Fernandes, Gabriela
Published: (2025)
by: Fernandes, Gabriela
Published: (2025)
Multi-modal Knowledge Decomposition based Online Distillation for Biomarker Prediction in Breast Cancer Histopathology
by: Zhang, Qibin, et al.
Published: (2025)
by: Zhang, Qibin, et al.
Published: (2025)
Expert-aware uncertainty estimation for quality control of neural-based blood typing
by: Zaychenkova, Ekaterina, et al.
Published: (2024)
by: Zaychenkova, Ekaterina, et al.
Published: (2024)
Interpretable Deep Transfer Learning for Breast Ultrasound Cancer Detection: A Multi-Dataset Study
by: Abbadi, Mohammad, et al.
Published: (2025)
by: Abbadi, Mohammad, et al.
Published: (2025)
Deep Learning for Breast Cancer Detection: Comparative Analysis of ConvNeXT and EfficientNet
by: Hasan, Mahmudul
Published: (2025)
by: Hasan, Mahmudul
Published: (2025)
Case-level Breast Cancer Prediction for Real Hospital Settings
by: Pathak, Shreyasi, et al.
Published: (2023)
by: Pathak, Shreyasi, et al.
Published: (2023)
Multimodal Stepwise Clinically-Guided Attention Learning for Pathological Complete Response Prediction in Breast Cancer
by: Caragliano, Alice Natalina, et al.
Published: (2026)
by: Caragliano, Alice Natalina, et al.
Published: (2026)
Enhancing Breast Cancer Diagnosis in Mammography: Evaluation and Integration of Convolutional Neural Networks and Explainable AI
by: Ahmed, Maryam, et al.
Published: (2024)
by: Ahmed, Maryam, et al.
Published: (2024)
Foundation Models for Slide-level Cancer Subtyping in Digital Pathology
by: Meseguer, Pablo, et al.
Published: (2024)
by: Meseguer, Pablo, et al.
Published: (2024)
CAMIL: Context-Aware Multiple Instance Learning for Cancer Detection and Subtyping in Whole Slide Images
by: Fourkioti, Olga, et al.
Published: (2023)
by: Fourkioti, Olga, et al.
Published: (2023)
A Deep Learning Approach for Virtual Contrast Enhancement in Contrast Enhanced Spectral Mammography
by: Rofena, Aurora, et al.
Published: (2023)
by: Rofena, Aurora, et al.
Published: (2023)
Bridging Accuracy and Interpretability: Deep Learning with XAI for Breast Cancer Detection
by: Chhetri, Bishal, et al.
Published: (2025)
by: Chhetri, Bishal, et al.
Published: (2025)
Hierarchical Perfusion Graphs for Tumor Heterogeneity Modeling in Glioma Molecular Subtyping
by: Jang, Han, et al.
Published: (2026)
by: Jang, Han, et al.
Published: (2026)
Similar Items
-
BI-RADS prediction of mammographic masses using uncertainty information extracted from a Bayesian Deep Learning model
by: Chegini, Mohaddeseh, et al.
Published: (2025) -
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification
by: Chegini, Mohaddeseh, et al.
Published: (2025) -
Modifying the U-Net's Encoder-Decoder Architecture for Segmentation of Tumors in Breast Ultrasound Images
by: Derakhshandeh, Sina, et al.
Published: (2024) -
Spatial Multi-Task Learning for Breast Cancer Molecular Subtype Prediction from Single-Phase DCE-MRI
by: Zeng, Sen, et al.
Published: (2026) -
MV-MLM: Bridging Multi-View Mammography and Language for Breast Cancer Diagnosis and Risk Prediction
by: Zheng, Shunjie-Fabian, et al.
Published: (2025)