A systematic review on the use of explainability in deep learning systems for computer aided diagnosis in radiology: Limited use of explainable AI?

Trust, regulation, and human-in-the-loop AI

(2022) Stuart E. Middleton et al.   COMMUNICATIONS OF THE ACM

One step further into the blackbox: a pilot study of how to build more confidence around an AI-based decision system of breast nodule assessment in 2D ultrasound

(2021) Fajin Dong et al.   EUROPEAN RADIOLOGY

Translation of predictive modeling and AI into clinics: a question of trust

(2021) Julian Caspers   EUROPEAN RADIOLOGY

AI in medicine must be explainable

(2021) Shinjini Kundu   NATURE MEDICINE

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

Evaluating explainable artificial intelligence methods for multi-label deep learning classification tasks in remote sensing

(2021) Ioannis Kakogeorgiou et al.   International Journal of Applied Earth Observation and Geoinformation

A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems

(2021) Sina Mohseni et al.   ACM Transactions on Interactive Intelligent Systems

Explainable artificial intelligence and machine learning: A reality rooted perspective

(2020) Frank Emmert‐Streib et al.   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

A qualitative research framework for the design of user-centered displays of explanations for machine learning model predictions in healthcare

(2020) Amie J. Barda et al.   BMC Medical Informatics and Decision Making

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

Causability and explainabilty of artificial intelligence in medicine

(2019) Andreas Holzinger et al.   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization

(2019) Ramprasaath R. Selvaraju et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Artificial Intelligence-Based Thyroid Nodule Classification Using Information from Spatial and Frequency Domains

(2019) Dat Tien Nguyen et al.   Journal of Clinical Medicine

Illuminating Clues of Cancer Buried in Prostate MR Image: Deep Learning and Expert Approaches

(2019) Jun Akatsuka et al.   Biomolecules

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

(2019) Alejandro Barredo Arrieta et al.   Information Fusion

Methods for interpreting and understanding deep neural networks

(2018) Grégoire Montavon et al.   DIGITAL SIGNAL PROCESSING

Deep Learning: A Primer for Radiologists

(2017) Gabriel Chartrand et al.   RADIOGRAPHICS

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

(2015) Sebastian Bach et al.   PLoS One