A Scoping Review of Interpretability and Explainability concerning Artificial Intelligence Methods in Medical Imaging
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Title
A Scoping Review of Interpretability and Explainability concerning Artificial Intelligence Methods in Medical Imaging
Authors
Keywords
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Journal
EUROPEAN JOURNAL OF RADIOLOGY
Volume -, Issue -, Pages 111159
Publisher
Elsevier BV
Online
2023-10-21
DOI
10.1016/j.ejrad.2023.111159
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Note: Only part of the references are listed.- An Interpretable Machine Learning Model to Predict Cortical Atrophy in Multiple Sclerosis
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- (2022) Modupe Odusami et al. SENSORS
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- (2022) Jayaraman J. Thiagarajan et al. Scientific Reports
- COVID detection from Chest X-Ray Images using multi-scale attention
- (2022) Abhinav Dhere et al. IEEE Journal of Biomedical and Health Informatics
- Multimodal Brain Connectomics-Based Prediction of Parkinson’s Disease Using Graph Attention Networks
- (2022) Apoorva Safai et al. Frontiers in Neuroscience
- Explainable machine learning with pairwise interactions for the classification of Parkinson’s disease and SWEDD from clinical and imaging features
- (2022) Alessia Sarica et al. Brain Imaging and Behavior
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- (2022) Jin Liu et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Attention module improves both performance and interpretability of four‐dimensional functional magnetic resonance imaging decoding neural network
- (2022) Zhoufan Jiang et al. HUMAN BRAIN MAPPING
- Interpretable Machine Learning for Characterization of Focal Liver Lesions by Contrast-Enhanced Ultrasound
- (2022) Simona Turco et al. IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL
- An interpretable radiomics model for the diagnosis of panic disorder with or without agoraphobia using magnetic resonance imaging
- (2022) Minji Bang et al. JOURNAL OF AFFECTIVE DISORDERS
- Development and Validation of a Visually Explainable Deep Learning Model for Classification of C-shaped Canals of the Mandibular Second Molars in Periapical and Panoramic Dental Radiographs
- (2022) Sujin Yang et al. JOURNAL OF ENDODONTICS
- Automated pneumothorax triaging in chest X‐rays in the New Zealand population using deep‐learning algorithms
- (2022) Sijing Feng et al. Journal of Medical Imaging and Radiation Oncology
- Voxel‐wise supervised analysis of tumors with multimodal engineered features to highlight interpretable biological patterns
- (2022) Thibault Escobar et al. MEDICAL PHYSICS
- A multi-sequences MRI deep framework study applied to glioma classfication
- (2022) Matthieu Coupet et al. MULTIMEDIA TOOLS AND APPLICATIONS
- A Single Model Deep Learning Approach for Alzheimer’s Disease Diagnosis
- (2022) Fan Zhang et al. NEUROSCIENCE
- Explainable AI for CNN-based prostate tumor segmentation in multi-parametric MRI correlated to whole mount histopathology
- (2022) Deepa Darshini Gunashekar et al. Radiation Oncology
- A Two-Stage Model for Predicting Mild Cognitive Impairment to Alzheimer’s Disease Conversion
- (2022) Peixin Lu et al. Frontiers in Aging Neuroscience
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- (2022) Mohamed Sobhi Jabal et al. Frontiers in Neurology
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- (2022) Loveleen Gaur et al. Frontiers in Genetics
- Cluster activation mapping with application to computed tomography scans of the lung
- (2022) Sarah M. Ryan et al. Journal of Medical Imaging
- Explaining a deep learning based breast ultrasound image classifier with saliency maps
- (2022) Michał Byra et al. Journal of Ultrasonography
- Explainable artificial intelligence-based edge fuzzy images for COVID-19 detection and identification
- (2022) Qinhua Hu et al. APPLIED SOFT COMPUTING
- 3D convolutional neural networks with hybrid attention mechanism for early diagnosis of Alzheimer’s disease
- (2022) Zhiwei Qin et al. Biomedical Signal Processing and Control
- Explainable machine learning approach to predict and explain the relationship between task-based fMRI and individual differences in cognition
- (2022) Narun Pat et al. CEREBRAL CORTEX
- The effect of machine learning explanations on user trust for automated diagnosis of COVID-19
- (2022) Kanika Goel et al. COMPUTERS IN BIOLOGY AND MEDICINE
- Interpretable ensemble deep learning model for early detection of Alzheimer's disease using local interpretable model‐agnostic explanations
- (2022) Atefe Aghaei et al. INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY
- Explainable artificial intelligence approach in combating real-time surveillance of COVID19 pandemic from CT scan and X-ray images using ensemble model
- (2022) Farhan Ullah et al. JOURNAL OF SUPERCOMPUTING
- Explainable artificial intelligence (XAI) in deep learning-based medical image analysis
- (2022) Bas H.M. van der Velden et al. MEDICAL IMAGE ANALYSIS
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- (2022) Gurmail Singh NEURAL NETWORKS
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- (2022) Mark C. Walker et al. PLoS One
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- (2022) Cameron Severn et al. SENSORS
- Multimodal deep learning for Alzheimer’s disease dementia assessment
- (2022) Shangran Qiu et al. Nature Communications
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- (2022) Ni Liao et al. IEEE Journal of Biomedical and Health Informatics
- COVID-19 Classification from Chest X-Ray Images: A Framework of Deep Explainable Artificial Intelligence
- (2022) Muhammad Attique Khan et al. Computational Intelligence and Neuroscience
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- (2022) Christian Tinauer et al. Scientific Reports
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- (2022) Yihang Wang et al. IEEE Journal of Biomedical and Health Informatics
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- Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning
- (2021) Hammam Alshazly et al. SENSORS
- An Interpretation Architecture for Deep Learning Models with the Application of COVID-19 Diagnosis
- (2021) Yuchai Wan et al. Entropy
- Opening the black box of AI‐Medicine
- (2021) Aaron I F Poon et al. JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY
- Human-recognizable CT image features of subsolid lung nodules associated with diagnosis and classification by convolutional neural networks
- (2021) Beibei Jiang et al. EUROPEAN RADIOLOGY
- Grad-CAM helps interpret the deep learning models trained to classify multiple sclerosis types using clinical brain magnetic resonance imaging
- (2021) Yunyan Zhang et al. JOURNAL OF NEUROSCIENCE METHODS
- Prospective assessment of breast cancer risk from multimodal multiview ultrasound images via clinically applicable deep learning
- (2021) Xuejun Qian et al. Nature Biomedical Engineering
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- (2021) Matteo Pennisi et al. ARTIFICIAL INTELLIGENCE IN MEDICINE
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- MANet: A two-stage deep learning method for classification of COVID-19 from Chest X-ray images
- (2021) Yujia Xu et al. NEUROCOMPUTING
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- COVID-19 Automatic Diagnosis With Radiographic Imaging: Explainable Attention Transfer Deep Neural Networks
- (2021) Wenqi Shi et al. IEEE Journal of Biomedical and Health Informatics
- Explainable Deep Learning for Personalized Age Prediction With Brain Morphology
- (2021) Angela Lombardi et al. Frontiers in Neuroscience
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- (2021) Weimin Tan et al. Annals of Translational Medicine
- CSGBBNet: An Explainable Deep Learning Framework for COVID-19 Detection
- (2021) Xu-Jing Yao et al. Diagnostics
- Object or Background: An Interpretable Deep Learning Model for COVID-19 Detection from CT-Scan Images
- (2021) Gurmail Singh et al. Diagnostics
- Machine Learning Evidence for Sex Differences Consistently Influences Resting-State fMRI Fluctuations Across Multiple Independently-Acquired Datasets
- (2021) Obada Al Zoubi et al. Brain Connectivity
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- (2021) Aniket Joshi et al. Journal of Medical Imaging
- Transparency and the Black Box Problem: Why We Do Not Trust AI
- (2021) Warren J. von Eschenbach Philosophy and Technology
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- (2021) Ambeshwar Kumar et al. ACM Transactions on Multimedia Computing Communications and Applications
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- (2021) Saeed Mohagheghi et al. COMPUTERS IN BIOLOGY AND MEDICINE
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- (2021) Kai Zhang et al. COMPUTERS IN BIOLOGY AND MEDICINE
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- (2021) Md. Rafiul Hassan et al. Future Generation Computer Systems-The International Journal of eScience
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- (2021) Hao Guan et al. HUMAN BRAIN MAPPING
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- (2021) Selcuk Kucukseymen et al. JOURNAL OF MAGNETIC RESONANCE IMAGING
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- (2021) Quan Zhang et al. Journal of Neural Engineering
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- (2021) Weilin He et al. KNOWLEDGE-BASED SYSTEMS
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- (2021) Cristian Alfonso Jimenez-Castaño et al. SENSORS
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- (2021) Shu-Cheng Liu et al. CANCER IMAGING
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- (2021) Majid Vafaeezadeh et al. International Journal of Computer Assisted Radiology and Surgery
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- (2021) Prashant Sadashiv Gidde et al. Scientific Reports
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- (2021) Mahmood Nazari et al. Scientific Reports
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- (2021) Jinkui Hao et al. Frontiers in Oncology
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- (2021) Morteza Esmaeili et al. Journal of Personalized Medicine
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- (2021) Shu-Hui Wang et al. Insights into Imaging
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- (2020) Parth Natekar et al. Frontiers in Computational Neuroscience
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- (2020) Gidon Levakov et al. HUMAN BRAIN MAPPING
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- (2020) Nikos Tsiknakis et al. Experimental and Therapeutic Medicine
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- (2020) Sophia Y. Wang et al. CURRENT OPINION IN OPHTHALMOLOGY
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- (2020) Carlo Biffi et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
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- (2020) Zhongyi Han et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Brain MRI analysis using a deep learning based evolutionary approach
- (2020) Hossein Shahamat et al. NEURAL NETWORKS
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- (2020) Paul Windisch et al. NEURORADIOLOGY
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- (2020) Xi Wei et al. MEDICAL SCIENCE MONITOR
- The natural language explanation algorithms for the lung cancer computer-aided diagnosis system
- (2020) Anna Meldo et al. ARTIFICIAL INTELLIGENCE IN MEDICINE
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- (2020) Plamen Angelov et al. NEURAL NETWORKS
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- (2020) Bas H. M. van der Velden et al. Scientific Reports
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- (2020) Ryutaro Tanno et al. NEUROIMAGE
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- (2020) Alina Lopatina et al. Frontiers in Neuroscience
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- (2020) Hayden Gunraj et al. Frontiers in Medicine
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- (2020) Xi Ouyang et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
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- (2019) Shiwen Shen et al. EXPERT SYSTEMS WITH APPLICATIONS
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- (2019) Naeim Bahrami et al. MAGNETIC RESONANCE IN MEDICINE
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- (2019) Clinton J. Wang et al. EUROPEAN RADIOLOGY
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- (2019) Moritz Böhle et al. Frontiers in Aging Neuroscience
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- (2019) Fabian Eitel et al. NeuroImage-Clinical
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- (2019) W. James Murdoch et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
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- (2018) Sérgio Pereira et al. MEDICAL IMAGE ANALYSIS
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- (2018) Athanasios Gotsopoulos et al. NEUROIMAGE
- PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation
- (2018) Andrea C. Tricco et al. ANNALS OF INTERNAL MEDICINE
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- (2018) Amina Adadi et al. IEEE Access
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- (2018) Tim Miller ARTIFICIAL INTELLIGENCE
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- (2017) Geert Litjens et al. MEDICAL IMAGE ANALYSIS
- PET-CT in Radiation Oncology
- (2009) Dwight E. Heron et al. AMERICAN JOURNAL OF CLINICAL ONCOLOGY-CANCER CLINICAL TRIALS
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