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

Feasibility and evaluation of a large-scale external validation approach for patient-level prediction in an international data network: validation of models predicting stroke in female patients newly diagnosed with atrial fibrillation

(2020) Jenna M. Reps et al.   BMC Medical Research Methodology

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

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

Application of Single-Nucleotide Polymorphisms in the Diagnosis of Autism Spectrum Disorders: A Preliminary Study with Artificial Neural Networks

(2019) Soudeh Ghafouri-Fard et al.   JOURNAL OF MOLECULAR NEUROSCIENCE

Machine Learning Interpretability: A Survey on Methods and Metrics

(2019) Diogo V. Carvalho et al.   Electronics

Definitions, methods, and applications in interpretable machine learning

(2019) W. James Murdoch et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Machine Learning, Predictive Analytics, and Clinical Practice

(2019) Eric D. Peterson   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

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

Measuring the Stability of Results from Supervised Statistical Learning

(2018) Michel Philipp et al.   JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS

Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data

(2018) Jenna M Reps et al.   JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION

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

(2018) Amina Adadi et al.   IEEE Access

The practical implementation of artificial intelligence technologies in medicine

(2018) Jianxing He et al.   NATURE MEDICINE

High-performance medicine: the convergence of human and artificial intelligence

(2018) Eric J. Topol   NATURE MEDICINE

Explanation in artificial intelligence: Insights from the social sciences

(2018) Tim Miller   ARTIFICIAL INTELLIGENCE

Distribution-Free Predictive Inference for Regression

(2017) Jing Lei et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Explaining nonlinear classification decisions with deep Taylor decomposition

(2017) Grégoire Montavon et al.   PATTERN RECOGNITION

Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review

(2016) Benjamin A Goldstein et al.   JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION

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

Validation of a common data model for active safety surveillance research

(2011) J Marc Overhage et al.   JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION

An empirical evaluation of the comprehensibility of decision table, tree and rule based predictive models

(2010) Johan Huysmans et al.   DECISION SUPPORT SYSTEMS

The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration

(2009) Alessandro Liberati et al.   JOURNAL OF CLINICAL EPIDEMIOLOGY

Predictive learning via rule ensembles

(2008) Jerome H. Friedman et al.   Annals of Applied Statistics