Copertina

Deep Modeling and Interpretation for Bladder Cancer Classification

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chaddad, Ahmad, Wu, Yihang, Chen, Xianrui
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Federated CLIP for Resource-Efficient Heterogeneous Medical Image Classification
di: Wu, Yihang, et al.
Pubblicazione: (2025)

Deep Modeling and Optimization of Medical Image Classification
di: Wu, Yihang, et al.
Pubblicazione: (2025)

Towards a Transparent and Interpretable AI Model for Medical Image Classifications
di: Wen, Binbin, et al.
Pubblicazione: (2025)

Impact of domain adaptation in deep learning for medical image classifications
di: Wu, Yihang, et al.
Pubblicazione: (2026)

GazeFormer-MoE: Context-Aware Gaze Estimation via CLIP and MoE Transformer
di: Zhao, Xinyuan, et al.
Pubblicazione: (2026)

Domain Adaptation Techniques for Natural and Medical Image Classification
di: Chaddad, Ahmad, et al.
Pubblicazione: (2025)

FACMIC: Federated Adaptative CLIP Model for Medical Image Classification
di: Wu, Yihang, et al.
Pubblicazione: (2024)

Classification based deep learning models for lung cancer and disease using medical images
di: Chaddad, Ahmad, et al.
Pubblicazione: (2025)

Federated Vision Transformer with Adaptive Focal Loss for Medical Image Classification
di: Zhao, Xinyuan, et al.
Pubblicazione: (2026)

Semi-Supervised Medical Image Segmentation via Dual Networks
di: Lu, Yunyao, et al.
Pubblicazione: (2025)

Generalizable and Explainable Deep Learning for Medical Image Computing: An Overview
di: Chaddad, Ahmad, et al.
Pubblicazione: (2025)

Enhancing Dual Network Based Semi-Supervised Medical Image Segmentation with Uncertainty-Guided Pseudo-Labeling
di: Lu, Yunyao, et al.
Pubblicazione: (2025)

GMGaze: MoE-Based Context-Aware Gaze Estimation with CLIP and Multiscale Transformer
di: Zhao, Xinyuan, et al.
Pubblicazione: (2026)

SHAP-Integrated Convolutional Diagnostic Networks for Feature-Selective Medical Analysis
di: Hu, Yan, et al.
Pubblicazione: (2025)

DeepHistoViT: An Interpretable Vision Transformer Framework for Histopathological Cancer Classification
di: Mosalpuri, Ravi, et al.
Pubblicazione: (2026)

A Quantitative Approach for Evaluating Disease Focus and Interpretability of Deep Learning Models for Alzheimer's Disease Classification
di: Tam, Thomas Yu Chow, et al.
Pubblicazione: (2024)

Deep Transfer Learning for Breast Cancer Classification
di: Djagba, Prudence, et al.
Pubblicazione: (2024)

Exploring the Efficacy of Group-Normalization in Deep Learning Models for Alzheimer's Disease Classification
di: Habib, Gousia, et al.
Pubblicazione: (2024)

FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography
di: Yang, Julia, et al.
Pubblicazione: (2024)

Enhanced Multi-Class Classification of Gastrointestinal Endoscopic Images with Interpretable Deep Learning Model
di: Kamble, Astitva, et al.
Pubblicazione: (2025)

Performance Comparison of Deep Learning Techniques in Naira Classification
di: Tijjani, Ismail Ismail, et al.
Pubblicazione: (2024)

Bayesian Evidential Learning for Few-Shot Classification
di: Linghu, Xiongkun, et al.
Pubblicazione: (2022)

Interpretable Aneurysm Classification via 3D Concept Bottleneck Models: Integrating Morphological and Hemodynamic Clinical Features
di: Khaled, Toqa, et al.
Pubblicazione: (2026)

Dynamic Neural Radiance Field From Defocused Monocular Video
di: Luo, Xianrui, et al.
Pubblicazione: (2024)

Vision Transformer-Based Deep Learning for Histologic Classification of Endometrial Cancer
di: Goyal, Manu, et al.
Pubblicazione: (2023)

Advancing Head and Neck Cancer Survival Prediction via Multi-Label Learning and Deep Model Interpretation
di: Chen, Meixu, et al.
Pubblicazione: (2024)

DTGBrepGen: A Novel B-rep Generative Model through Decoupling Topology and Geometry
di: Li, Jing, et al.
Pubblicazione: (2025)

H-CNN-ViT: A Hierarchical Gated Attention Multi-Branch Model for Bladder Cancer Recurrence Prediction
di: Li, Xueyang, et al.
Pubblicazione: (2025)

Dual-Camera All-in-Focus Neural Radiance Fields
di: Luo, Xianrui, et al.
Pubblicazione: (2025)

Advancing Multiple Instance Learning with Continual Learning for Whole Slide Imaging
di: Li, Xianrui, et al.
Pubblicazione: (2025)

A Deep Learning Method for Classification of Biophilic Artworks
di: Kar, Purna, et al.
Pubblicazione: (2024)

Using Computer Vision for Skin Disease Diagnosis in Bangladesh Enhancing Interpretability and Transparency in Deep Learning Models for Skin Cancer Classification
di: Islam, Rafiul, et al.
Pubblicazione: (2025)

Interpretable Deep Transfer Learning for Breast Ultrasound Cancer Detection: A Multi-Dataset Study
di: Abbadi, Mohammad, et al.
Pubblicazione: (2025)

Dynamic Memory Transformer for Hyperspectral Image Classification
di: Ahmad, Muhammad
Pubblicazione: (2025)

Concepts in Motion: Temporal Concept Bottleneck Model for Interpretable Video Classification
di: Knab, Patrick, et al.
Pubblicazione: (2025)

NMGrad: Advancing Histopathological Bladder Cancer Grading with Weakly Supervised Deep Learning
di: Fuster, Saul, et al.
Pubblicazione: (2024)

A Novel Hybrid Deep Learning and Chaotic Dynamics Approach for Thyroid Cancer Classification
di: Bouchekout, Nada, et al.
Pubblicazione: (2025)

How Far Can We Compress Instant-NGP-Based NeRF?
di: Chen, Yihang, et al.
Pubblicazione: (2024)

ProtoSolo: Interpretable Image Classification via Single-Prototype Activation
di: Peng, Yitao, et al.
Pubblicazione: (2025)

Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation
di: K, Sikha O, et al.
Pubblicazione: (2025)