A Systematic Review of Human–Computer Interaction and Explainable Artificial Intelligence in Healthcare With Artificial Intelligence Techniques

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

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Artificial intelligence in healthcare: past, present and future

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XAI—Explainable artificial intelligence

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SecureML: A System for Scalable Privacy-Preserving Machine Learning

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The effects of explainability and causability on perception, trust, and acceptance: Implications for explainable AI

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DARPA's Explainable Artificial Intelligence Program

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Explainable artificial intelligence: A survey

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Machine learning & artificial intelligence in the quantum domain: a review of recent progress

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Effect of confidence and explanation on accuracy and trust calibration in AI-assisted decision making

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Bridging the Gap Between Ethics and Practice: Guidelines for Reliable, Safe, and Trustworthy Human-centered AI Systems

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

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Technology acceptance theories and factors influencing artificial Intelligence-based intelligent products

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Explainable machine learning in deployment

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Artificial Intelligence in Health Care: A Report From the National Academy of Medicine

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Artificial Intelligence Transforms the Future of Health Care

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From high-touch to high-tech: COVID-19 drives robotics adoption

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Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey

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Managing computational complexity using surrogate models: a critical review

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User Perceptions of Algorithmic Decisions in the Personalized AI System:Perceptual Evaluation of Fairness, Accountability, Transparency, and Explainability

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Human-centred design in global health: A scoping review of applications and contexts

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Privacy-Preserving Machine Learning: Threats and Solutions

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Legal, regulatory, and ethical frameworks for development of standards in artificial intelligence (AI) and autonomous robotic surgery

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Artificial intelligence, machine learning and deep learning

Ongsulee, P. (2017) · International Conference on ICT and Knowledge Engineering · doi:10.1109/ictke.2017.8259629 · Cited by 392 · see citing works

A Survey of the State of Explainable AI for Natural Language Processing

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A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence

Stepin, I., Alonso, J. M., Catala, A., & Pereira-Farina, M. (2021) · IEEE Access · doi:10.1109/access.2021.3051315 · Cited by 376 · see citing works

Explaining Recurrent Neural Network Predictions in Sentiment Analysis

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Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era

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Explainable artificial intelligence models using real-world electronic health record data: a systematic scoping review

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Fairness in Machine Learning

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The relationship between trust in AI and trustworthy machine learning technologies

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Counterfactuals in Explainable Artificial Intelligence (XAI): Evidence from Human Reasoning

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One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques

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explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning

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Explainable Artificial Intelligence for 6G: Improving Trust between Human and Machine

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A Trustworthy Privacy Preserving Framework for Machine Learning in Industrial IoT Systems

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Explainability as a non-functional requirement: challenges and recommendations

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Human factors in model interpretability: Industry practices, challenges, and needs

Hong, S. R., Hullman, J., & Bertini, E. (2020) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3392878 · Cited by 219 · see citing works

Usability Studies on Mobile User Interface Design Patterns: A Systematic Literature Review

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Simulation-based Adversarial Test Generation for Autonomous Vehicles with Machine Learning Components

Tuncali, C. E., Fainekos, G., Ito, H., & Kapinski, J. P. (2018) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2018.8500421 · Cited by 207 · see citing works

A Systematic Review on Monitoring and Advanced Control Strategies in Smart Agriculture

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A Survey of Automated Text Simplification

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The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations

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Explainable Artificial Intelligence: Concepts, Applications, Research Challenges and Visions

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Explanation in AI and law: Past, present and future

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Explainable AI in Healthcare

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Chiron: Privacy-preserving Machine Learning as a ServicePreprint

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The Impact of Placebic Explanations on Trust in Intelligent Systems

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HCI for health and wellbeing: Challenges and opportunities

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Blockchain for explainable and trustworthy artificial intelligence

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Explainable AI for Healthcare: From Black Box to Interpretable Models

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Mapping Machine Learning Advances from HCI Research to Reveal Starting Places for Design Innovation

Yang, Q., Banović, N., & Zimmerman, J. (2018) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173704 · Cited by 130 · see citing works

Requirements-driven test generation for autonomous vehicles with machine learning components

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Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure

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Mapping Human–Computer Interaction Research Themes and Trends from Its Existence to Today: A Topic Modeling-Based Review of past 60 Years

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Human–computer interaction-based Decision Support System with Applications in Data Mining

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Accountable algorithms? The ethical implications of data-driven business models

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Explainable Machine Learning Algorithms For Predicting Glass Transition Temperatures

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Mitigating Poisoning Attacks on Machine Learning Models: A Data Provenance Based Approach

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The Emerging Landscape of Explainable Automated Planning & Decision Making

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A Comprehensive Study of Load Balancing Approaches in the Cloud Computing Environment and a Novel Fault Tolerance Approach

Shahid, M. A., Islam, N., Alam, M. M., et al. (2020) · IEEE Access · doi:10.1109/access.2020.3009184 · Cited by 105 · see citing works

Explainable AI meets Healthcare: A Study on Heart Disease DatasetPreprint

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Evaluating local explanation methods on ground truth

Guidotti, R. (2020) · Artificial Intelligence · doi:10.1016/j.artint.2020.103428 · Cited by 99 · see citing works

Artificial intelligence in healthcare in developing nations: The beginning of a transformative journey

Mahajan, A., Vaidya, T. P., Gupta, A., Rane, S. U., & Gupta, S. (2019) · Cancer Research Statistics and Treatment · doi:10.4103/crst.crst_50_19 · Cited by 95 · see citing works

A “Third Wheel” Effect in Health Decision Making Involving Artificial Entities: A Psychological Perspective

Triberti, S., Durosini, I., & Pravettoni, G. (2020) · Frontiers in Public Health · doi:10.3389/fpubh.2020.00117 · Cited by 89 · see citing works

On cognitive preferences and the plausibility of rule-based models

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State Of The Art: A Study of Human-Robot Interaction in Healthcare

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Impact of usability mechanisms: An experiment on efficiency, effectiveness and user satisfaction

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A systematic review of software usability studies

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Towards Resilient Method: An exhaustive survey of fault tolerance methods in the cloud computing environment

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Combining e‐mental health intervention development with human computer interaction ( <scp>HCI</scp> ) design to enhance technology‐facilitated recovery for people with depression and/or anxiety conditions: An integrative literature review

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A Survey on Deep Learning for Steering Angle Prediction in Autonomous Vehicles

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Human-centered design of complex systems: An experience-based approach

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Explainable Artificial Intelligence (XAI): An Engineering PerspectivePreprint

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A Situation Awareness-Based Framework for Design and Evaluation of Explainable AI

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Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach

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Explainable Text-Driven Neural Network for Stock Prediction

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An overview of healthcare improvement: unpacking the complexity for clinicians and managers in a learning health system

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QATCH - An adaptive framework for software product quality assessment

Siavvas, M., Chatzidimitriou, K. C., & Symeonidis, A. L. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2017.05.060 · Cited by 48 · see citing works

Understanding end-users' perspectives: Towards developing usability guidelines for disaster apps

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Incorporating Explainable Artificial Intelligence (XAI) to aid Understanding of Machine Learning in the Healthcare Domain

Pawar, U., O’Shea, D., Rea, S., & O’Reilly, R. (2020) · doi:10.13140/rg.2.2.24754.02246 · Cited by 45 · see citing works

Privacy-Preserving Scoring of Tree Ensembles: A Novel Framework for AI in Healthcare

Fritchman, K., Saminathan, K., Dowsley, R., Hughes, T., Cock, M. D., Nascimento, A. C. A., & Teredesai, A. M. (2018) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2018.8622627 · Cited by 44 · see citing works

Lithuanian case study on evaluating suitability, acceptance and use of IT tools by students – An example of applying Technology Enhanced Learning Research methods in Higher Education

Kurilovas, E., & Kubilinskienė, S. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106274 · Cited by 41 · see citing works

A new wave of innovation in Semantic web tools for drug discovery

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On Adversarial Bias and the Robustness of Fair Machine LearningPreprint

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Explainable Text Classification in Legal Document Review A Case Study of Explainable Predictive Coding

Chhatwal, R., Gronvall, P., Huber-Fliflet, N., Keeling, R., Zhang, J., & Zhao, H. (2018) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2018.8622073 · Cited by 37 · see citing works

Declarative Aspects in Explicative Data Mining for Computational Sensemaking

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A Type-2 Fuzzy Logic Approach to Explainable AI for regulatory compliance, fair customer outcomes and market stability in the Global Financial Sector

Adams, J., & Hagras, H. (2020) · 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) · doi:10.1109/fuzz48607.2020.9177542 · Cited by 35 · see citing works

What Do You See? Evaluation of Explainable Artificial Intelligence (XAI) Interpretability through Neural BackdoorsPreprint

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Business Intelligence for Enterprise Internet of Things

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Impact of Human-Centered Design Process (HCDP) on Software Development Process

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A Performance-Explainability Framework to Benchmark Machine Learning Methods: Application to Multivariate Time Series ClassifiersPreprint

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Innovative prototypes for cervical cancer prevention in low-income primary care settings: A human-centered design approach

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Thoughts on human-computer interaction in the age of artificial intelligence

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Critical Factors for Human Computer Interaction of eHealth for Older Adults

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Development of Artificial Intelligence by Ensembles of Virtual Agents with Mobile Interaction

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Editable machine learning models? A rule-based framework for user studies of explainability

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BlockFLA: Accountable Federated Learning via Hybrid Blockchain ArchitecturePreprint

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Continuous Software Engineering with Special Emphasis on Continuous Business-Process Modeling and Human-Centered Design

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White, Grey, Black: Effects of XAI Augmentation on the Confidence in AI-based Decision Support Systems

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Human Computer Interaction Trends in Healthcare: An Update

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Human-Centered Design for Collaborative Innovation in Knowledge-based Economies

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Explainable Artificial Intelligence Applications in Cyber Security: State-of-the-Art in Research

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How Explainable Artificial Intelligence Can Increase or Decrease Clinicians’ Trust in AI Applications in Health Care: Systematic Review

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