Katrien Verbert
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View article: Importance of User Control in Data-Centric Steering for Healthcare Experts
Importance of User Control in Data-Centric Steering for Healthcare Experts Open
As Artificial Intelligence (AI) becomes increasingly integrated into high-stakes domains like healthcare, effective collaboration between healthcare experts and AI systems is critical. Data-centric steering, which involves fine-tuning pred…
View article: Petal-x Visualization for Lifestyle Change in Patients at Risk of Cardiovascular Diseases: An Evaluation
Petal-x Visualization for Lifestyle Change in Patients at Risk of Cardiovascular Diseases: An Evaluation Open
Cardiovascular diseases (CVDs) are the leading global cause of death and addressing unhealthy lifestyles is essential for reducing CVD risk. Visual explanations, such as the Petal-X dashboard, can support personalized care by improving pat…
View article: Visual-Conversational Interface for Evidence-Based Explanation of Diabetes Risk Prediction
Visual-Conversational Interface for Evidence-Based Explanation of Diabetes Risk Prediction Open
Healthcare professionals need effective ways to use, understand, and validate AI-driven clinical decision support systems. Existing systems face two key limitations: complex visualizations and a lack of grounding in scientific evidence. We…
View article: Visual-Conversational Interface for Evidence-Based Explanation of Diabetes Risk Prediction
Visual-Conversational Interface for Evidence-Based Explanation of Diabetes Risk Prediction Open
Healthcare professionals need effective ways to use, understand, and validate AI-driven clinical decision support systems. Existing systems face two key limitations: complex visualizations and a lack of grounding in scientific evidence. We…
View article: A Systematic Review of User-Centred Evaluation of Explainable AI in Healthcare
A Systematic Review of User-Centred Evaluation of Explainable AI in Healthcare Open
Despite promising developments in Explainable Artificial Intelligence, the practical value of XAI methods remains under-explored and insufficiently validated in real-world settings. Robust and context-aware evaluation is essential, not onl…
View article: Video Games and Gamification for Assessing Mild Cognitive Impairment: Scoping Review
Video Games and Gamification for Assessing Mild Cognitive Impairment: Scoping Review Open
Background Early assessment of mild cognitive impairment (MCI) in older adults is crucial, as it enables timely interventions and decision-making. In recent years, researchers have been exploring the potential of gamified interactive syste…
View article: Granular Feedback: Leveraging Domain Expertise and Explainable AI to Effectively Steer Models
Granular Feedback: Leveraging Domain Expertise and Explainable AI to Effectively Steer Models Open
sponsorship: We would like to thank ZAVO, and Joke Vandepitte in particular, for allowing us to collaborate. We would like to thank FWO by facilitating this interdisciplinary research. Additionally, we would like to thank all participants …
View article: "Show Me How": Benefits and Challenges of Agent-Augmented Counterfactual Explanations for Non-Expert Users
"Show Me How": Benefits and Challenges of Agent-Augmented Counterfactual Explanations for Non-Expert Users Open
Counterfactual explanations offer actionable insights by illustrating how changes to inputs can lead to different outcomes. However, these explanations often suffer from ambiguity and impracticality, limiting their utility for non-expert u…
View article: Disentangling Stakeholder Role and Expertise in User-Centered Explainable AI
Disentangling Stakeholder Role and Expertise in User-Centered Explainable AI Open
sponsorship: We would like to thank all participants for their time and valuable insights. This research is part of the research projects funded by CAPTURE (grant HBC.2024.0220), KU Leuven (grant C14/21/072) and the Research Foundation Fla…
View article: Let's Get You Hired: A Job Seeker's Perspective on Multi-Agent Recruitment Systems for Explaining Hiring Decisions
Let's Get You Hired: A Job Seeker's Perspective on Multi-Agent Recruitment Systems for Explaining Hiring Decisions Open
During job recruitment, traditional applicant selection methods often lack transparency. Candidates are rarely given sufficient justifications for recruiting decisions, whether they are made manually by human recruiters or through the use …
View article: Will Health Experts Adopt a Clinical Decision Support System for Game-Based Digital Biomarkers? Investigating the Impact of Different Explanations on Perceived Ease-of-Use, Perceived Usefulness, and Trust
Will Health Experts Adopt a Clinical Decision Support System for Game-Based Digital Biomarkers? Investigating the Impact of Different Explanations on Perceived Ease-of-Use, Perceived Usefulness, and Trust Open
status: Published online
View article: Designing Visual Explanations and Learner Controls to Engage Adolescents in AI-Supported Exercise Selection
Designing Visual Explanations and Learner Controls to Engage Adolescents in AI-Supported Exercise Selection Open
E-learning platforms that personalise content selection with AI are often criticised for lacking transparency and controllability. Researchers have therefore proposed solutions such as open learner models and letting learners select from r…
View article: Video Games and Gamification for Assessing Mild Cognitive Impairment: Scoping Review (Preprint)
Video Games and Gamification for Assessing Mild Cognitive Impairment: Scoping Review (Preprint) Open
BACKGROUND Early assessment of mild cognitive impairment (MCI) in older adults is crucial, as it enables timely interventions and decision-making. In recent years, researchers have been exploring the potential of gamified interactive syst…
View article: AI Innovations in rPPG Systems for Driver Monitoring: Comprehensive Systematic Review and Future Prospects
AI Innovations in rPPG Systems for Driver Monitoring: Comprehensive Systematic Review and Future Prospects Open
Advanced technologies, notably camera-based systems using remote photoplethysmography (rPPG), are increasingly used in automotive safety to non-invasively monitor driver well-being and fatigue by measuring physiological metrics like heart …
View article: Explanatory Debiasing: Involving Domain Experts in the Data Generation Process to Mitigate Representation Bias in AI Systems
Explanatory Debiasing: Involving Domain Experts in the Data Generation Process to Mitigate Representation Bias in AI Systems Open
Representation bias is one of the most common types of biases in artificial intelligence (AI) systems, causing AI models to perform poorly on underrepresented data segments. Although AI practitioners use various methods to reduce represent…
View article: An Explanation Interface for Healthy Food Recommendations in a Real-Life Workplace Deployment: User-Centered Design Study
An Explanation Interface for Healthy Food Recommendations in a Real-Life Workplace Deployment: User-Centered Design Study Open
Background Despite widespread awareness of healthy eating principles, many individuals struggle to translate this knowledge into consistent, sustainable dietary change. Food recommender systems, increasingly used in various settings, offer…
View article: The Role of Visualization in Estimating Cardiovascular Disease Risk: Scoping Review
The Role of Visualization in Estimating Cardiovascular Disease Risk: Scoping Review Open
Background Supporting and understanding the health of patients with chronic diseases and cardiovascular disease (CVD) risk is often a major challenge. Health data are often used in providing feedback to patients, and visualization plays an…
View article: A Method for Developing Process-Based Assessments for Computational Thinking Tasks
A Method for Developing Process-Based Assessments for Computational Thinking Tasks Open
Computational thinking (CT) is a concept of growing importance to pre-university education. Yet, CT is often assessed through results, rather than by looking at the CT process itself. Process-based assessments, or assessments that model ho…
View article: Representation Debiasing of Generated Data Involving Domain Experts
Representation Debiasing of Generated Data Involving Domain Experts Open
Biases in Artificial Intelligence (AI) or Machine Learning (ML) systems due\nto skewed datasets problematise the application of prediction models in\npractice. Representation bias is a prevalent form of bias found in the majority\nof datas…
View article: "How Good Is Your Explanation?": Towards a Standardised Evaluation Approach for Diverse XAI Methods on Multiple Dimensions of Explainability
"How Good Is Your Explanation?": Towards a Standardised Evaluation Approach for Diverse XAI Methods on Multiple Dimensions of Explainability Open
Artificial Intelligence (AI) systems involve diverse components, such as data, models, users and predicted outcomes. To elucidate these different aspects of AI systems, multifaceted explanations that combine diverse explainable AI (XAI) me…
View article: An Explanatory Model Steering System for Collaboration between Domain Experts and AI
An Explanatory Model Steering System for Collaboration between Domain Experts and AI Open
With the increasing adoption of Artificial Intelligence (AI) systems in\nhigh-stake domains, such as healthcare, effective collaboration between domain\nexperts and AI is imperative. To facilitate effective collaboration between\ndomain ex…
View article: Petal-X: Human-Centered Visual Explanations to Improve Cardiovascular Risk Communication
Petal-X: Human-Centered Visual Explanations to Improve Cardiovascular Risk Communication Open
Cardiovascular diseases (CVDs), the leading cause of death worldwide, can be prevented in most cases through behavioral interventions. Therefore, effective communication of CVD risk and projected risk reduction by risk factor modification …
View article: Representation Debiasing of Generated Data Involving Domain Experts
Representation Debiasing of Generated Data Involving Domain Experts Open
Biases in Artificial Intelligence (AI) or Machine Learning (ML) systems due to skewed datasets problematise the application of prediction models in practice. Representation bias is a prevalent form of bias found in the majority of datasets…
View article: "How Good Is Your Explanation?": Towards a Standardised Evaluation Approach for Diverse XAI Methods on Multiple Dimensions of Explainability
"How Good Is Your Explanation?": Towards a Standardised Evaluation Approach for Diverse XAI Methods on Multiple Dimensions of Explainability Open
Artificial Intelligence (AI) systems involve diverse components, such as data, models, users and predicted outcomes. To elucidate these different aspects of AI systems, multifaceted explanations that combine diverse explainable AI (XAI) me…
View article: Designing and Evaluating Explanations for a Predictive Health Dashboard: A User-Centred Case Study
Designing and Evaluating Explanations for a Predictive Health Dashboard: A User-Centred Case Study Open
As predictive health technologies become increasingly prevalent, the need for effective explanations that aid health experts and practitioners in understanding the underlying factors driving predictions is paramount. While many different e…
View article: EXMOS: Explanatory Model Steering through Multifaceted Explanations and Data Configurations
EXMOS: Explanatory Model Steering through Multifaceted Explanations and Data Configurations Open
Explanations in interactive machine-learning systems facilitate debugging and improving prediction models. However, the effectiveness of various global model-centric and data-centric explanations in aiding domain experts to detect and reso…
View article: The Role of Visualization in Estimating Cardiovascular Disease Risk: Scoping Review (Preprint)
The Role of Visualization in Estimating Cardiovascular Disease Risk: Scoping Review (Preprint) Open
BACKGROUND Supporting and understanding the health of patients with chronic diseases and cardiovascular disease (CVD) risk is often a major challenge. Health data are often used in providing feedback to patients, and visualization plays a…
View article: The effect of personalizing a psychotherapy conversational agent on therapeutic bond and usage intentions
The effect of personalizing a psychotherapy conversational agent on therapeutic bond and usage intentions Open
sponsorship: We would like to thank all participants for their time and valuable insights. This research is financed by the Research Foundation Flanders (FWO) with project numbers G0A4923N and G067721N, as well as the KU Leuven C1 grant wi…