{"total":83,"rows":[{"id":"2404.10237","title":"Med-MoE: Mixture of Domain-Specific Experts for Lightweight Medical Vision-Language Models","created":"2024-04-16","cited_by_count":46,"area":"mllm"},{"id":"2111.08164","title":"A Survey on Neural-symbolic Learning Systems","created":"2021-11-10","cited_by_count":39,"area":null},{"id":"2212.05946","title":"Evaluation and Improvement of Interpretability for Self-Explainable Part-Prototype Networks","created":"2022-12-12","cited_by_count":37,"area":null},{"id":"2205.04766","title":"Explainable Deep Learning Methods in Medical Image Classification: A Survey","created":"2022-05-10","cited_by_count":32,"area":null},{"id":"2307.10504","title":"Identifying Interpretable Subspaces in Image Representations","created":"2023-07-20","cited_by_count":32,"area":null},{"id":"2112.12596","title":"Explainable Medical Imaging AI Needs Human-Centered Design: Guidelines and Evidence from a Systematic Review","created":"2021-12-21","cited_by_count":30,"area":null},{"id":"2312.15010","title":"SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology","created":"2023-12-22","cited_by_count":25,"area":null},{"id":"2404.15022","title":"A review of deep learning-based information fusion techniques for multimodal medical image classification","created":"2024-04-23","cited_by_count":25,"area":null},{"id":"2211.05667","title":"What Makes a Good Explanation?: A Harmonized View of Properties of Explanations","created":"2022-11-10","cited_by_count":22,"area":null},{"id":"2412.01496","title":"Fr\\'echet Radiomic Distance (FRD): A Versatile Metric for Comparing Medical Imaging Datasets","created":"2024-12-02","cited_by_count":19,"area":null},{"id":"2410.02331","title":"Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks","created":"2024-10-03","cited_by_count":18,"area":null},{"id":"2203.10417","title":"Attri-VAE: attribute-based interpretable representations of medical images with variational autoencoders","created":"2022-03-20","cited_by_count":17,"area":null},{"id":"2407.15851","title":"A Survey on Trustworthiness in Foundation Models for Medical Image Analysis","created":"2024-07-03","cited_by_count":17,"area":null},{"id":"2307.12463","title":"Rethinking Data Distillation: Do Not Overlook Calibration","created":"2023-07-24","cited_by_count":13,"area":null},{"id":"2307.10404","title":"Interpreting and Correcting Medical Image Classification with PIP-Net","created":"2023-07-19","cited_by_count":11,"area":null},{"id":"2403.13111","title":"Deep learning with noisy labels in medical prediction problems: a scoping review","created":"2024-03-19","cited_by_count":10,"area":null},{"id":"2407.04370","title":"Regulating Model Reliance on Non-Robust Features by Smoothing Input Marginal Density","created":"2024-07-05","cited_by_count":10,"area":null},{"id":"2307.04569","title":"Interpreting and generalizing deep learning in physics-based problems with functional linear models","created":"2023-07-10","cited_by_count":9,"area":null},{"id":"2310.01685","title":"A Framework for Interpretability in Machine Learning for Medical Imaging","created":"2023-10-02","cited_by_count":9,"area":null},{"id":"2312.07965","title":"Pneumonia Detection on chest X-ray images Using Ensemble of Deep Convolutional Neural Networks","created":"2023-12-13","cited_by_count":9,"area":null},{"id":"2312.00192","title":"Benchmarking and Enhancing Disentanglement in Concept-Residual Models","created":"2023-11-30","cited_by_count":5,"area":null},{"id":"2309.15857","title":"A Survey on Image-text Multimodal Models","created":"2023-09-23","cited_by_count":4,"area":null},{"id":"2402.18211","title":"Catastrophic Overfitting: A Potential Blessing in Disguise","created":"2024-02-28","cited_by_count":4,"area":null},{"id":"2207.00157","title":"Improving Disease Classification Performance and Explainability of Deep Learning Models in Radiology with Heatmap Generators","created":"2022-06-28","cited_by_count":3,"area":null},{"id":"2403.18328","title":"PIPNet3D: Interpretable Detection of Alzheimer in MRI Scans","created":"2024-03-27","cited_by_count":3,"area":null},{"id":"2404.00144","title":"An Interpretable Cross-Attentive Multi-modal MRI Fusion Framework for Schizophrenia Diagnosis","created":"2024-03-29","cited_by_count":3,"area":null},{"id":"2502.05214","title":"CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models","created":"2025-02-04","cited_by_count":3,"area":null},{"id":"2504.19179","title":"A Design Framework for operationalizing Trustworthy Artificial Intelligence in Healthcare: Requirements, Tradeoffs and Challenges for its Clinical Adoption","created":"2025-04-27","cited_by_count":3,"area":null},{"id":"2508.10869","title":"Medico 2025: Visual Question Answering for Gastrointestinal Imaging","created":"2025-08-14","cited_by_count":3,"area":null},{"id":"2509.14780","title":"Radiology Report Conditional 3D CT Generation with Multi Encoder Latent diffusion Model","created":"2025-09-18","cited_by_count":3,"area":"diffusion"},{"id":"2206.13608","title":"Reducing Annotation Need in Self-Explanatory Models for Lung Nodule Diagnosis","created":"2022-06-27","cited_by_count":2,"area":null},{"id":"2310.16332","title":"Corrupting Neuron Explanations of Deep Visual Features","created":"2023-10-25","cited_by_count":2,"area":null},{"id":"2406.04039","title":"Shaping History: Advanced Machine Learning Techniques for the Analysis and Dating of Cuneiform Tablets over Three Millennia","created":"2024-06-06","cited_by_count":2,"area":null},{"id":"2407.13813","title":"A review of handcrafted and deep radiomics in neurological diseases: transitioning from oncology to clinical neuroimaging","created":"2024-07-18","cited_by_count":2,"area":null},{"id":"2411.10686","title":"MaskMedPaint: Masked Medical Image Inpainting with Diffusion Models for Mitigation of Spurious Correlations","created":"2024-11-16","cited_by_count":2,"area":"diffusion"},{"id":"2511.12008","title":"Adaptive Diagnostic Reasoning Framework for Pathology with Multimodal Large Language Models","created":"2025-11-15","cited_by_count":2,"area":"lr"},{"id":"2208.07981","title":"Tiny-HR: Towards an interpretable machine learning pipeline for heart rate estimation on edge devices","created":"2022-08-16","cited_by_count":1,"area":null},{"id":"2210.16097","title":"cRedAnno+: Annotation Exploitation in Self-Explanatory Lung Nodule Diagnosis","created":"2022-10-28","cited_by_count":1,"area":null},{"id":"2404.08917","title":"MAProtoNet: A Multi-scale Attentive Interpretable Prototypical Part Network for 3D Magnetic Resonance Imaging Brain Tumor Classification","created":"2024-04-13","cited_by_count":1,"area":null},{"id":"2405.14720","title":"Convolutional Neural Network Model Observers Discount Signal-like Anatomical Structures During Search in Virtual Digital Breast Tomosynthesis Phantoms","created":"2024-05-23","cited_by_count":1,"area":null},{"id":"2406.08695","title":"Global AI Governance in Healthcare: A Cross-Jurisdictional Regulatory Analysis","created":"2024-06-12","cited_by_count":1,"area":null},{"id":"2408.03789","title":"Counterfactuals and Uncertainty-Based Explainable Paradigm for the Automated Detection and Segmentation of Renal Cysts in Computed Tomography Images: A Multi-Center Study","created":"2024-08-07","cited_by_count":1,"area":null},{"id":"2409.11110","title":"Beyond accuracy: quantifying the reliability of Multiple Instance Learning for Whole Slide Image classification","created":"2024-09-17","cited_by_count":1,"area":null},{"id":"2411.04354","title":"Impact of white noise in artificial neural networks trained for classification: performance and noise mitigation strategies","created":"2024-11-07","cited_by_count":1,"area":null},{"id":"2501.08962","title":"An analysis of data variation and bias in image-based dermatological datasets for machine learning classification","created":"2025-01-15","cited_by_count":1,"area":null},{"id":"2504.21457","title":"xEEGNet: Towards Explainable AI in EEG Dementia Classification","created":"2025-04-30","cited_by_count":1,"area":null},{"id":"2507.07148","title":"Explainable Artificial Intelligence in Biomedical Image Analysis: A Comprehensive Survey","created":"2025-07-09","cited_by_count":1,"area":null},{"id":"2508.09478","title":"GazeLT: Visual attention-guided long-tailed disease classification in chest radiographs","created":"2025-08-13","cited_by_count":1,"area":null},{"id":"2509.19980","title":"RAD: Towards Trustworthy Retrieval-Augmented Multi-modal Clinical Diagnosis","created":"2025-09-24","cited_by_count":1,"area":"rag"},{"id":"2511.02152","title":"ProtoTSNet: Interpretable Multivariate Time Series Classification With Prototypical Parts","created":"2025-11-04","cited_by_count":1,"area":null},{"id":"2208.00953","title":"Visual Interpretable and Explainable Deep Learning Models for Brain Tumor MRI and COVID-19 Chest X-ray Images","created":"2022-08-01","cited_by_count":0,"area":null},{"id":"2212.06299","title":"Interpretable Diabetic Retinopathy Diagnosis based on Biomarker Activation Map","created":"2022-12-13","cited_by_count":0,"area":null},{"id":"2212.10877","title":"TMS-Net: A Segmentation Network Coupled With A Run-time Quality Control Method For Robust Cardiac Image Segmentation","created":"2022-12-21","cited_by_count":0,"area":null},{"id":"2307.08003","title":"SHAMSUL: Systematic Holistic Analysis to investigate Medical Significance Utilizing Local interpretability methods in deep learning for chest radiography pathology prediction","created":"2023-07-16","cited_by_count":0,"area":null},{"id":"2401.17200","title":"NormEnsembleXAI: Unveiling the Strengths and Weaknesses of XAI Ensemble Techniques","created":"2024-01-30","cited_by_count":0,"area":null},{"id":"2405.07670","title":"Impact of white Gaussian internal noise on analog echo-state neural networks","created":"2024-05-13","cited_by_count":0,"area":null},{"id":"2406.00555","title":"Length-scale study in deep learning prediction for non-small cell lung cancer brain metastasis","created":"2024-06-01","cited_by_count":0,"area":null},{"id":"2407.11375","title":"Mask-Free Neuron Concept Annotation for Interpreting Neural Networks in Medical Domain","created":"2024-07-16","cited_by_count":0,"area":null},{"id":"2408.03771","title":"Methodological Explainability Evaluation of an Interpretable Deep Learning Model for Post-Hepatectomy Liver Failure Prediction Incorporating Counterfactual Explanations and Layerwise Relevance Propagation: A Prospective In Silico Trial","created":"2024-08-07","cited_by_count":0,"area":null},{"id":"2409.15374","title":"Explainable AI for Autism Diagnosis: Identifying Critical Brain Regions Using fMRI Data","created":"2024-09-19","cited_by_count":0,"area":null},{"id":"2410.03188","title":"Looking into Concept Explanation Methods for Diabetic Retinopathy Classification","created":"2024-10-04","cited_by_count":0,"area":null},{"id":"2411.10255","title":"Artificial Intelligence in Pediatric Echocardiography: Exploring Challenges, Opportunities, and Clinical Applications with Explainable AI and Federated Learning","created":"2024-11-15","cited_by_count":0,"area":null},{"id":"2412.03352","title":"Intuitive Axial Augmentation Using Polar-Sine-Based Piecewise Distortion for Medical Slice-Wise Segmentation","created":"2024-12-04","cited_by_count":0,"area":null},{"id":"2501.17813","title":"P-TAME: Explain Any Image Classifier with Trained Perturbations","created":"2025-01-29","cited_by_count":0,"area":null},{"id":"2503.20230","title":"TraNCE: Transformative Non-linear Concept Explainer for CNNs","created":"2025-03-26","cited_by_count":0,"area":null},{"id":"2504.10080","title":"Learning to Harmonize Cross-vendor X-ray Images by Non-linear Image Dynamics Correction","created":"2025-04-14","cited_by_count":0,"area":null},{"id":"2504.19357","title":"MERA: Multimodal and Multiscale Self-Explanatory Model with Considerably Reduced Annotation for Lung Nodule Diagnosis","created":"2025-04-27","cited_by_count":0,"area":null},{"id":"2505.15120","title":"Lung Nodule-SSM: Self-Supervised Lung Nodule Detection and Classification in Thoracic CT Images","created":"2025-05-21","cited_by_count":0,"area":null},{"id":"2505.17971","title":"Explainable Anatomy-Guided AI for Prostate MRI: Foundation Models and In Silico Clinical Trials for Virtual Biopsy-based Risk Assessment","created":"2025-05-23","cited_by_count":0,"area":null},{"id":"2506.10669","title":"PiPViT: Patch-based Visual Interpretable Prototypes for Retinal Image Analysis","created":"2025-06-12","cited_by_count":0,"area":null},{"id":"2507.08690","title":"An Efficient Approach for Muscle Segmentation and 3D Reconstruction Using Keypoint Tracking in MRI Scan","created":"2025-07-11","cited_by_count":0,"area":null},{"id":"2509.10510","title":"FireGNN: Neuro-Symbolic Graph Neural Networks with Trainable Fuzzy Rules for Interpretable Medical Image Classification","created":"2025-09-02","cited_by_count":0,"area":null},{"id":"2509.10523","title":"From Predictions to Explanations: Explainable AI for Autism Diagnosis and Identification of Critical Brain Regions","created":"2025-09-04","cited_by_count":0,"area":null},{"id":"2601.07585","title":"Robust Multicentre Detection and Classification of Colorectal Liver Metastases on CT: Application of Foundation Models","created":"2026-01-12","cited_by_count":0,"area":null},{"id":"2601.08604","title":"Interpretability and Individuality in Knee MRI: Patient-Specific Radiomic Fingerprint with Reconstructed Healthy Personas","created":"2026-01-13","cited_by_count":0,"area":null},{"id":"2601.15042","title":"Federated Transformer-GNN for Privacy-Preserving Brain Tumor Localization with Modality-Level Explainability","created":"2026-01-21","cited_by_count":0,"area":null},{"id":"2603.02235","title":"Talking with Verifiers: Automatic Specification Generation for Neural Network Verification","created":"2026-02-13","cited_by_count":0,"area":null},{"id":"2604.11868","title":"MedConcept: Unsupervised Concept Discovery for Interpretability in Medical VLMs","created":"2026-04-13","cited_by_count":0,"area":"mllm"},{"id":"2606.02035","title":"RL-ACRGNet: Reinforcement Learning-Based Chest Radiology Report Generation Network","created":"2026-06-01","cited_by_count":0,"area":null},{"id":"2607.09779","title":"A Generalized Deep Non-negative Matrix Factorization Approach for SAR Automatic Target Recognition","created":"2026-07-08","cited_by_count":0,"area":null},{"id":"2608.14725","title":"Spatial Attention Noise Masking for Causally Sufficient Interpretability","created":"2026-08-12","cited_by_count":0,"area":null},{"id":"2609.12724","title":"Prism-SQA: An Interpretable and Adaptable Neural Framework for Surface Electromyography Quality Assessment","created":"2026-09-11","cited_by_count":0,"area":null},{"id":"2609.17753","title":"Beyond Performance Metrics: Uncertainty Mapping of Label Ambiguity in Fazekas Score Prediction","created":"2026-09-15","cited_by_count":0,"area":null}],"next_cursor":null}