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03/15/2023
Pixel-Level Explanation of Multiple Instance Learning Models in Biomedical Single Cell Images
Explainability is a key requirement for computer-aided diagnosis systems...
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07/15/2022
CheXplaining in Style: Counterfactual Explanations for Chest X-rays using StyleGAN
Deep learning models used in medical image analysis are prone to raising...
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03/30/2022
Interpretable Vertebral Fracture Diagnosis
Do black-box neural network models learn clinically relevant features fo...
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03/29/2022
Few-shot Structured Radiology Report Generation Using Natural Language Prompts
Chest radiograph reporting is time-consuming, and numerous solutions to ...
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03/04/2022
Do Explanations Explain? Model Knows Best
It is a mystery which input features contribute to a neural network's ou...
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10/04/2021
Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information
One principal approach for illuminating a black-box neural network is fe...
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04/04/2021
Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models
Convolutional neural networks are showing promise in the automatic diagn...
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04/01/2021
Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features
Neural networks have demonstrated remarkable performance in classificati...
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03/31/2021
Neural Response Interpretation through the Lens of Critical Pathways
Is critical input information encoded in specific sparse pathways within...
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03/12/2021
Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs
Chest computed tomography (CT) has played an essential diagnostic role i...
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12/01/2020
Rethinking Positive Aggregation and Propagation of Gradients in Gradient-based Saliency Methods
Saliency methods interpret the prediction of a neural network by showing...
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04/07/2020
Spatio-temporal Learning from Longitudinal Data for Multiple Sclerosis Lesion Segmentation
Segmentation of Multiple Sclerosis (MS) lesions in longitudinal brain MR...
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11/25/2019
Explaining Neural Networks via Perturbing Important Learned Features
Attributing the output of a neural network to the contribution of given ...
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05/09/2019
