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Painting the Black Box White: Experimental Findings from Applying XAI to an ECG Reading Setting
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Biases Affecting Human Decision Making in AI-Supported Second Opinion Settings
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Color Shadows (Part I): Exploratory Usability Evaluation of Activation Maps in Radiological Machine Learning
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Explainable AI: The New 42?
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Accurate classification of ECG arrhythmia using MOWPT enhanced fast compression deep learning networks
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Generating Explanations for Conceptual Validation of Graph Neural Networks: An Investigation of Symbolic Predicates Learned on Relevance-Ranked Sub-Graphs
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Computer-based consultations in clinical therapeutics: Explanation and rule acquisition capabilities of the MYCIN system
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Wizard of Oz studies — why and how
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An extension of the theory of technology dominance: Capturing the underlying causal complexity
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Explanation in artificial intelligence: Insights from the social sciences
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A review on deep learning methods for ECG arrhythmia classification
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The perils and pitfalls of explainable AI: Strategies for explaining algorithmic decision-making
inferredcites →https://doi.org/10.1016/j.ijhcs.2020.102551openalex-snapshot
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The need to move away from agential-AI: Empirical investigations, useful concepts and open issues
inferredcites →https://doi.org/10.1016/j.inffus.2019.12.012openalex-snapshot
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
inferredcites →https://doi.org/10.1016/j.inffus.2021.05.009openalex-snapshot
Notions of explainability and evaluation approaches for explainable artificial intelligence
inferredcites →https://doi.org/10.1016/j.jarmac.2015.07.001openalex-snapshot
A naturalistic decision making perspective on studying intuitive decision making.
inferredcites →https://doi.org/10.1016/j.jelectrocard.2021.07.003openalex-snapshot
Machine learning with electrocardiograms: A call for guidelines and best practices for ‘stress testing’ algorithms
inferredcites →https://doi.org/10.1016/j.knosys.2021.107763openalex-snapshot
Designing ECG monitoring healthcare system with federated transfer learning and explainable AI
inferredcites →https://doi.org/10.1016/j.ymeth.2021.04.021openalex-snapshot
Automated ECG classification based on 1D deep learning network
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Do tax decision support systems affect the accuracy of tax compliance decisions?
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The false hope of current approaches to explainable artificial intelligence in health care
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The mindlessness of ostensibly thoughtful action: The role of "placebic" information in interpersonal interaction.
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How machine-learning recommendations influence clinician treatment selections: the example of antidepressant selection
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Explainable machine-learning predictions for the prevention of hypoxaemia during surgery
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Experimental evidence of effective human–AI collaboration in medical decision-making
inferredcites →https://doi.org/10.1038/s41746-021-00385-9openalex-snapshot
Do as AI say: susceptibility in deployment of clinical decision-aids
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Siri, Alexa, and other digital assistants: a study of customer satisfaction with artificial intelligence applications
inferredcites →https://doi.org/10.1080/10447318.2020.1741118openalex-snapshot
Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy
inferredcites →https://doi.org/10.1080/1463922x.2022.2061080openalex-snapshot
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Impact of explainable artificial intelligence assistance on clinical decision-making of novice dental clinicians
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Toward Human–AI Interfaces to Support Explainability and Causability in Medical AI
inferredcites →https://doi.org/10.1111/j.1467-629x.2004.00099.xopenalex-snapshot
Impact of intelligent decision aids on expert and novice decision‐makers’ judgments
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Human error: models and management
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The Impact of Placebic Explanations on Trust in Intelligent Systems
inferredcites →https://doi.org/10.1145/3301275.3308446openalex-snapshot
DARPA's explainable artificial intelligence (XAI) program
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From Human-Human Collaboration to Human-AI Collaboration
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Effect of confidence and explanation on accuracy and trust calibration in AI-assisted decision making
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The Effects of Mixing Machine Learning and Human Judgment
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The Principles and Limits of Algorithm-in-the-Loop Decision Making
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Misplaced Trust: Measuring the Interference of Machine Learning in Human Decision-Making
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Manipulating and Measuring Model Interpretability
inferredcites →https://doi.org/10.1145/3411764.3445717openalex-snapshot
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance
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Will Algorithms Blind People? The Effect of Explainable AI and Decision-Makers’ Experience on AI-supported Decision-Making in Government
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Cronbach’s Coefficient Alpha
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inferredcites →https://doi.org/10.2139/ssrn.3691575openalex-snapshot
When Algorithms Err: Differential Impact of Early vs. Late Errors on Users' Reliance on Algorithms
inferredcites →https://doi.org/10.2196/28236openalex-snapshot
Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review
inferredcites →https://doi.org/10.24251/hicss.2019.034openalex-snapshot
The Future of Human-AI Collaboration: A Taxonomy of Design Knowledge for Hybrid Intelligence Systems
inferredcites →https://doi.org/10.24251/hicss.2021.156openalex-snapshot
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inferredcites →https://doi.org/10.2753/mis0742-1222270108openalex-snapshot
Technology Dominance in Complex Decision Making: The Case of Aided Credibility Assessment
inferredcites →https://doi.org/10.3233/ia-190036openalex-snapshot
On the integration of symbolic and sub-symbolic techniques for XAI: A survey
inferredcites →https://doi.org/10.3390/jintelligence9020017openalex-snapshot
Unity Is Intelligence: A Collective Intelligence Experiment on ECG Reading to Improve Diagnostic Performance in Cardiology
inferredcites →https://doi.org/10.48550/arxiv.1812.03219openalex-snapshot
Dice in the Black Box: User Experiences with an Inscrutable Algorithm
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-44064-9_33openalex-snapshot
Color Shadows 2: Assessing the Impact of XAI on Diagnostic Decision-Making
inferred← citeshttps://doi.org/10.1007/978-3-031-60606-9_16openalex-snapshot
Designing for Complementarity: A Conceptual Framework to Go Beyond the Current Paradigm of Using XAI in Healthcare
inferred← citeshttps://doi.org/10.1007/978-3-031-63803-9_14openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-67155-5_11openalex-snapshot
Human-Centered AI (Also) for Humanistic Management
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Trust Paradoxes in Machine Learning: An Ontological Approach
inferred← citeshttps://doi.org/10.1007/978-3-031-95838-0_14openalex-snapshot
Conformal Prediction for ECG Interpretation: A Study on Human-AI Collaboration in Clinical Decision Support
inferred← citeshttps://doi.org/10.1007/978-3-032-08317-3_11openalex-snapshot
Too Sure for Trust. The Paradoxical Effect of Calibrated Confidence in Case of Uncalibrated Trust in Hybrid Decision Making
inferred← citeshttps://doi.org/10.1007/978-3-032-19182-3_11openalex-snapshot
Unveiling the Black Box: Enhancing Acceptance and Trust in ECG Image-Based Cardiac Diagnosis, Employing Explainable AI Techniques
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inferred← citeshttps://doi.org/10.1016/j.artmed.2024.102819openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.compbiomed.2024.108042openalex-snapshot
Evidence-based XAI: An empirical approach to design more effective and explainable decision support systems
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2025.110944openalex-snapshot
Evaluating explanation performance for clinical decision support systems for non-imaging data: A systematic literature review
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Evaluating the Impact of Explainable AI on User Perceptions in Healthcare Chatbots for Celiac Disease Management
inferred← citeshttps://doi.org/10.1038/s43856-024-00568-xopenalex-snapshot
Explainable AI decision support improves accuracy during telehealth strep throat screening
inferred← citeshttps://doi.org/10.1055/a-2562-2163openalex-snapshot
Alternative Strategies to Generate Class Activation Maps Supporting AI-based Advice in Vertebral Fracture Detection in X-ray Images
inferred← citeshttps://doi.org/10.1080/10447318.2025.2574511openalex-snapshot
Don’t Be Fooled: The Misinformation Effect of Explanations in Human–AI Collaboration
inferred← citeshttps://doi.org/10.1080/10447318.2026.2676768openalex-snapshot
Investigating Machine Learning Accuracy, Type, and Explainability on Trust-Relevant Criteria: A Human-Centered Approach
inferred← citeshttps://doi.org/10.1093/9780198945215.003.0173openalex-snapshot
AI Personhood as Socially Designed and Enacted Interaction
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Development of a theoretical model for calibrating trust in AI to augment highways safety
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XAI Unveiled: Revealing the Potential of Explainable AI in Medicine - A Systematic Review
inferred← citeshttps://doi.org/10.1109/ai-si66213.2025.11341336openalex-snapshot
Using the K-Nearest Neighbor and Explainable Artificial Intelligence to Classify Arrhythmias
inferred← citeshttps://doi.org/10.1145/3742413.3789100openalex-snapshot
Design Considerations for Human Oversight of AI: Insights from Co-Design Workshops and Work Design Theory
inferred← citeshttps://doi.org/10.1145/3805689.3812265openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3816965openalex-snapshot
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inferred← citeshttps://doi.org/10.21203/rs.3.rs-10892043/v1openalex-snapshot
Clinical explainable AI evaluations prioritize trust over effective human oversight: a scoping review
inferred← citeshttps://doi.org/10.3389/fcomp.2024.1521066openalex-snapshot
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inferred← citeshttps://doi.org/10.33965/mccsis2023_202305l020openalex-snapshot
EXPLAINABLE ARTIFICIAL INTELLIGENCE IN THE DIAGNOSIS OF CARDIOVASCULAR DISEASES IN SMALL SAMPLES
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