Understanding and Interpreting Machine Learning in Medical Image Computing Applications
Overview of attention for book
Table of Contents
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Altmetric BadgeBook Overview
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Altmetric BadgeChapter 1 Alzheimer’s Disease Modelling and Staging Through Independent Gaussian Process Analysis of Spatio-Temporal Brain Changes
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Altmetric BadgeChapter 2 Multi-channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer’s Disease
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Altmetric BadgeChapter 3 Visualizing Convolutional Networks for MRI-Based Diagnosis of Alzheimer’s Disease
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Altmetric BadgeChapter 4 Finding Effective Ways to (Machine) Learn fMRI-Based Classifiers from Multi-site Data
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Altmetric BadgeChapter 5 Towards Robust CT-Ultrasound Registration Using Deep Learning Methods
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Altmetric BadgeChapter 6 To Learn or Not to Learn Features for Deformable Registration?
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Altmetric BadgeChapter 7 Evaluation of Strategies for PET Motion Correction - Manifold Learning vs. Deep Learning
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Altmetric BadgeChapter 8 Exploring Adversarial Examples
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Altmetric BadgeChapter 9 Shortcomings of Ventricle Segmentation Using Deep Convolutional Networks
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Altmetric BadgeChapter 10 Vulnerability Analysis of Chest X-Ray Image Classification Against Adversarial Attacks
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Altmetric BadgeChapter 11 Collaborative Human-AI (CHAI): Evidence-Based Interpretable Melanoma Classification in Dermoscopic Images
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Altmetric BadgeChapter 12 Automatic Brain Tumor Grading from MRI Data Using Convolutional Neural Networks and Quality Assessment
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Altmetric BadgeChapter 13 Visualizing Convolutional Neural Networks to Improve Decision Support for Skin Lesion Classification
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Altmetric BadgeChapter 14 Regression Concept Vectors for Bidirectional Explanations in Histopathology
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Altmetric BadgeChapter 15 Towards Complementary Explanations Using Deep Neural Networks
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Altmetric BadgeChapter 16 How Users Perceive Content-Based Image Retrieval for Identifying Skin Images
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About this Attention Score
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In the top 25% of all research outputs scored by Altmetric
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High Attention Score compared to outputs of the same age (92nd percentile)
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High Attention Score compared to outputs of the same age and source (97th percentile)
Citations
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