Survey of explainable artificial intelligence techniques for biomedical imaging with deep neural networks

ArtifactID: Identifying artifacts in low-field MRI of the brain using deep learning

(2022) Marina Manso Jimeno et al.   MAGNETIC RESONANCE IMAGING

Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning

(2021) Hammam Alshazly et al.   SENSORS

Detection of Cardiac Structural Abnormalities in Fetal Ultrasound Videos Using Deep Learning

(2021) Masaaki Komatsu et al.   Applied Sciences-Basel

Expl(AI)n It to Me – Explainable AI and Information Systems Research

(2021) Kevin Bauer et al.   Business & Information Systems Engineering

Correction to: Decoding COVID-19 pneumonia: comparison of deep learning and radiomics CT image signatures

(2021) Hongmei Wang et al.   EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING

Explaining decisions of graph convolutional neural networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer

(2021) Hryhorii Chereda et al.   Genome Medicine

Enterprise imaging and big data: A review from a medical physics perspective

(2021) Nicholas McCarthy et al.   Physica Medica-European Journal of Medical Physics

Artificial intelligence: Deep learning in oncological radiomics and challenges of interpretability and data harmonization

(2021) Panagiotis Papadimitroulas et al.   Physica Medica-European Journal of Medical Physics

Understanding inherent image features in CNN-based assessment of diabetic retinopathy

(2021) Roc Reguant et al.   Scientific Reports

A Review of Explainable Deep Learning Cancer Detection Models in Medical Imaging

(2021) Mehmet A. Gulum et al.   Applied Sciences-Basel

Prospective assessment of breast cancer risk from multimodal multiview ultrasound images via clinically applicable deep learning

(2021) Xuejun Qian et al.   Nature Biomedical Engineering

Using ontologies to enhance human understandability of global post-hoc explanations of black-box models

(2021) Roberto Confalonieri et al.   ARTIFICIAL INTELLIGENCE

An explainable AI system for automated COVID-19 assessment and lesion categorization from CT-scans

(2021) Matteo Pennisi et al.   ARTIFICIAL INTELLIGENCE IN MEDICINE

xECGNet: Fine-tuning attention map within convolutional neural network to improve detection and explainability of concurrent cardiac arrhythmias

(2021) Jungsun Yoo et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

A survey of visual analytics for Explainable Artificial Intelligence methods

(2021) Gulsum Alicioglu et al.   COMPUTERS & GRAPHICS-UK

Interpretable heartbeat classification using local model-agnostic explanations on ECGs

(2021) Inês Neves et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Ensembles of Convolutional Neural Network models for pediatric pneumonia diagnosis

(2021) Helena Liz et al.   Future Generation Computer Systems-The International Journal of eScience

Ten Open Challenges in Medical Visualization

(2021) Christina Gillmann et al.   IEEE COMPUTER GRAPHICS AND APPLICATIONS

Towards multi-modal causability with Graph Neural Networks enabling information fusion for explainable AI

(2021) Andreas Holzinger et al.   Information Fusion

AI for COVID-19 Detection from Radiographs: Incisive Analysis of State of the Art Techniques, Key Challenges and Future Directions

(2021) R. Karthik et al.   IRBM

Explaining Deep Learning using examples: Optimal feature weighting methods for twin systems using post-hoc, explanation-by-example in XAI

(2021) Eoin M. Kenny et al.   KNOWLEDGE-BASED SYSTEMS

ExplAIn: Explanatory artificial intelligence for diabetic retinopathy diagnosis

(2021) Gwenolé Quellec et al.   MEDICAL IMAGE ANALYSIS

Pruning by explaining: A novel criterion for deep neural network pruning

(2021) Seul-Ki Yeom et al.   PATTERN RECOGNITION

Current Challenges and Future Opportunities for XAI in Machine Learning-Based Clinical Decision Support Systems: A Systematic Review

(2021) Anna Markella Antoniadi et al.   Applied Sciences-Basel

Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging

(2021) Masaaki Komatsu et al.   Biomedicines

Black box algorithms and the rights of individuals: no easy solution to the “explainability” problem

(2021) Jarek Gryz et al.   Internet Policy Review

An Explainable Deep Learning Ensemble Model for Robust Diagnosis of Diabetic Retinopathy Grading

(2021) Mohammad Shorfuzzaman et al.   ACM Transactions on Multimedia Computing Communications and Applications

Doctor's Dilemma: Evaluating an Explainable Subtractive Spatial Lightweight Convolutional Neural Network for Brain Tumor Diagnosis

(2021) Ambeshwar Kumar et al.   ACM Transactions on Multimedia Computing Communications and Applications

Explainable AI to improve acceptance of convolutional neural networks for automatic classification of dopamine transporter SPECT in the diagnosis of clinically uncertain parkinsonian syndromes

(2021) Mahmood Nazari et al.   EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING

Prostate cancer classification from ultrasound and MRI images using deep learning based Explainable Artificial Intelligence

(2021) Md. Rafiul Hassan et al.   Future Generation Computer Systems-The International Journal of eScience

Parkinson’s Disease Recognition Using SPECT Image and Interpretable AI: A Tutorial

(2021) Theerasarn Pianpanit et al.   IEEE SENSORS JOURNAL

Guided Zoom: Zooming into Network Evidence to Refine Fine-Grained Model Decisions

(2021) Sarah Adel Bargal et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond

(2021) Guang Yang et al.   Information Fusion

Explaining clinical decision support systems in medical imaging using cycle-consistent activation maximization

(2021) Alexander Katzmann et al.   NEUROCOMPUTING

Towards robust explanations for deep neural networks

(2021) Ann-Kathrin Dombrowski et al.   PATTERN RECOGNITION

Automatic morphological classification of mitral valve diseases in echocardiographic images based on explainable deep learning methods

(2021) Majid Vafaeezadeh et al.   International Journal of Computer Assisted Radiology and Surgery

CLEVR-XAI: A benchmark dataset for the ground truth evaluation of neural network explanations

(2021) Leila Arras et al.   Information Fusion

EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: The MonuMAI cultural heritage use case

(2021) Natalia Díaz-Rodríguez et al.   Information Fusion

Offline computer-aided diagnosis for Glaucoma detection using fundus images targeted at mobile devices

(2020) José Martins et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Demystifying Brain Tumor Segmentation Networks: Interpretability and Uncertainty Analysis

(2020) Parth Natekar et al.   Frontiers in Computational Neuroscience

AppendiXNet: Deep Learning for Diagnosis of Appendicitis from A Small Dataset of CT Exams Using Video Pretraining

(2020) Pranav Rajpurkar et al.   Scientific Reports

From a deep learning model back to the brain—Identifying regional predictors and their relation to aging

(2020) Gidon Levakov et al.   HUMAN BRAIN MAPPING

Domain-invariant interpretable fundus image quality assessment

(2020) Yaxin Shen et al.   MEDICAL IMAGE ANALYSIS

Explainable skin lesion diagnosis using taxonomies

(2020) Catarina Barata et al.   PATTERN RECOGNITION

Computer-aided diagnosis for fetal brain ultrasound images using deep convolutional neural networks

(2020) Baihong Xie et al.   International Journal of Computer Assisted Radiology and Surgery

Automated coronary artery atherosclerosis detection and weakly supervised localization on coronary CT angiography with a deep 3-dimensional convolutional neural network

(2020) Sema Candemir et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Convolutional Neural Network ensembles for accurate lung nodule malignancy prediction 2 years in the future

(2020) Rahul Paul et al.   COMPUTERS IN BIOLOGY AND MEDICINE

CovXNet: A multi-dilation convolutional neural network for automatic COVID-19 and other pneumonia detection from chest X-ray images with transferable multi-receptive feature optimization

(2020) Tanvir Mahmud et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Explainable AI and Mass Surveillance System-Based Healthcare Framework to Combat COVID-I9 Like Pandemics

(2020) M. Shamim Hossain et al.   IEEE NETWORK

A Mutual Bootstrapping Model for Automated Skin Lesion Segmentation and Classification

(2020) Yutong Xie et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Explainable classifier for improving the accountability in decision-making for colorectal cancer diagnosis from histopatological images

(2020) Patrik Sabol et al.   JOURNAL OF BIOMEDICAL INFORMATICS

COVID-19 Pneumonia Diagnosis Using a Simple 2D Deep Learning Framework With a Single Chest CT Image: Model Development and Validation

(2020) Hoon Ko et al.   JOURNAL OF MEDICAL INTERNET RESEARCH

DR|GRADUATE: Uncertainty-aware deep learning-based diabetic retinopathy grading in eye fundus images

(2020) Teresa Araújo et al.   MEDICAL IMAGE ANALYSIS

Implementation of model explainability for a basic brain tumor detection using convolutional neural networks on MRI slices

(2020) Paul Windisch et al.   NEURORADIOLOGY

Multi-input deep learning architecture for predicting breast tumor response to chemotherapy using quantitative MR images

(2020) Mohammed El Adoui et al.   International Journal of Computer Assisted Radiology and Surgery

Detection of Parkinson’s Disease from 3T T1 Weighted MRI Scans Using 3D Convolutional Neural Network

(2020) Sabyasachi Chakraborty et al.   Diagnostics

HihO: accelerating artificial intelligence interpretability for medical imaging in IoT applications using hierarchical occlusion

(2020) William S. Monroe et al.   NEURAL COMPUTING & APPLICATIONS

Volumetric breast density estimation on MRI using explainable deep learning regression

(2020) Bas H. M. van der Velden et al.   Scientific Reports

Artificial Intelligence Algorithms to Diagnose Glaucoma and Detect Glaucoma Progression: Translation to Clinical Practice

(2020) Anna S. Mursch-Edlmayr et al.   Translational Vision Science & Technology

Artificial intelligence in radiology: relevance of collaborative work between radiologists and engineers for building a multidisciplinary team

(2020) T. Martín-Noguerol et al.   CLINICAL RADIOLOGY

Explainable AI: A Review of Machine Learning Interpretability Methods

(2020) Pantelis Linardatos et al.   Entropy

Improving the performance of CNN to predict the likelihood of COVID-19 using chest X-ray images with preprocessing algorithms

(2020) Morteza Heidari et al.   INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS

The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies

(2020) Aniek F. Markus et al.   JOURNAL OF BIOMEDICAL INFORMATICS

Investigation of Deep-Learning-Driven Identification of Multiple Sclerosis Patients Based on Susceptibility-Weighted Images Using Relevance Analysis

(2020) Alina Lopatina et al.   Frontiers in Neuroscience

HealthXAI: Collaborative and explainable AI for supporting early diagnosis of cognitive decline

(2020) Elham Khodabandehloo et al.   Future Generation Computer Systems-The International Journal of eScience

CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation

(2020) Ran Gu et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Explainability in deep reinforcement learning

(2020) Alexandre Heuillet et al.   KNOWLEDGE-BASED SYSTEMS

A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI

(2020) Erico Tjoa et al.   IEEE Transactions on Neural Networks and Learning Systems

Explainable artificial intelligence for breast cancer: a visual case-based reasoning approach

(2019) Jean-Baptiste Lamy et al.   ARTIFICIAL INTELLIGENCE IN MEDICINE

Artificial Intelligence and Black-Box Medical Decisions: Accuracy versus Explainability

(2019) Alex John London   HASTINGS CENTER REPORT

Artificial intelligence in breast imaging

(2019) E.P.V. Le et al.   CLINICAL RADIOLOGY

SDFN: Segmentation-based Deep Fusion Network for Thoracic Disease Classification in Chest X-ray Images

(2019) Han Liu et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features

(2019) Clinton J. Wang et al.   EUROPEAN RADIOLOGY

The Pragmatic Turn in Explainable Artificial Intelligence (XAI)

(2019) Andrés Páez   MINDS AND MACHINES

Automated semantic labeling of pediatric musculoskeletal radiographs using deep learning

(2019) Paul H. Yi et al.   PEDIATRIC RADIOLOGY

Causal Interpretations of Black-Box Models

(2019) Qingyuan Zhao et al.   JOURNAL OF BUSINESS & ECONOMIC STATISTICS

Exploiting hierarchical visual features for visual question answering

(2019) Jongkwang Hong et al.   NEUROCOMPUTING

Layer-Wise Relevance Propagation for Explaining Deep Neural Network Decisions in MRI-Based Alzheimer's Disease Classification

(2019) Moritz Böhle et al.   Frontiers in Aging Neuroscience

Medinoid: Computer-Aided Diagnosis and Localization of Glaucoma Using Deep Learning †

(2019) Mijung Kim et al.   Applied Sciences-Basel

The Missing Pieces of Artificial Intelligence in Medicine

(2019) Coryandar Gilvary et al.   TRENDS IN PHARMACOLOGICAL SCIENCES

Key challenges for delivering clinical impact with artificial intelligence

(2019) Christopher J. Kelly et al.   BMC Medicine

Cognitive signature of brain FDG PET based on deep learning: domain transfer from Alzheimer’s disease to Parkinson’s disease

(2019) Hongyoon Choi et al.   EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING

Toward an interpretable Alzheimer’s disease diagnostic model with regional abnormality representation via deep learning

(2019) Eunho Lee et al.   NEUROIMAGE

Blockchain for explainable and trustworthy artificial intelligence

(2019) Mohamed Nassar et al.   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

Data-efficient deep learning of radiological image data for outcome prediction after endovascular treatment of patients with acute ischemic stroke

(2019) A. Hilbert et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Shape and margin-aware lung nodule classification in low-dose CT images via soft activation mapping

(2019) Yiming Lei et al.   MEDICAL IMAGE ANALYSIS

Deep Learning Enables Automatic Classification of Emphysema Pattern at CT

(2019) Stephen M. Humphries et al.   RADIOLOGY

Deep learning enables pathologist-like scoring of NASH models

(2019) Fabian Heinemann et al.   Scientific Reports

Guided Soft Attention Network for Classification of Breast Cancer Histopathology Images

(2019) Heechan Yang et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis

(2019) WangMin Liao et al.   IEEE Journal of Biomedical and Health Informatics

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

(2019) Alejandro Barredo Arrieta et al.   Information Fusion

Lesion Location Attention Guided Network for Multi-Label Thoracic Disease Classification in Chest X-Rays

(2019) Bingzhi Chen et al.   IEEE Journal of Biomedical and Health Informatics

Pulmonary Textures Classification via a Multi-Scale Attention Network

(2019) Rui Xu et al.   IEEE Journal of Biomedical and Health Informatics

Laterality Classification of Fundus Images Using Interpretable Deep Neural Network

(2018) Yeonwoo Jang et al.   JOURNAL OF DIGITAL IMAGING

A Decision-Support Tool for Renal Mass Classification

(2018) Gautam Kunapuli et al.   JOURNAL OF DIGITAL IMAGING

A computational framework for the detection of subcortical brain dysmaturation in neonatal MRI using 3D Convolutional Neural Networks

(2018) Rafael Ceschin et al.   NEUROIMAGE

Detection and Classification of Cancer in Whole Slide Breast Histopathology Images Using Deep Convolutional Networks

(2018) Baris Gecer et al.   PATTERN RECOGNITION

A Survey of Methods for Explaining Black Box Models

(2018) Riccardo Guidotti et al.   ACM COMPUTING SURVEYS

Peeking inside the black-box: A survey on Explainable Artificial Intelligence (XAI)

(2018) Amina Adadi et al.   IEEE Access

Using a Deep Learning Algorithm and Integrated Gradients Explanation to Assist Grading for Diabetic Retinopathy

(2018) Rory Sayres et al.   OPHTHALMOLOGY

Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study

(2018) Ahmed Hosny et al.   PLOS MEDICINE

Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: A cross-sectional study

(2018) John R. Zech et al.   PLOS MEDICINE

Chest Radiographs in Congestive Heart Failure: Visualizing Neural Network Learning

(2018) Jarrel C. Y. Seah et al.   RADIOLOGY

Assessment of Convolutional Neural Networks for Automated Classification of Chest Radiographs

(2018) Jared A. Dunnmon et al.   RADIOLOGY

CNN Fixations: An Unraveling Approach to Visualize the Discriminative Image Regions

(2018) Konda Reddy Mopuri et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Top-Down Neural Attention by Excitation Backprop

(2017) Jianming Zhang et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Explaining nonlinear classification decisions with deep Taylor decomposition

(2017) Grégoire Montavon et al.   PATTERN RECOGNITION

Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation

(2015) Alex Goldstein et al.   JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS

On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

(2015) Sebastian Bach et al.   PLoS One

The Graph Neural Network Model

(2008) F. Scarselli et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS