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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 25

Will Health Experts Adopt a Clinical Decision Support System...

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30th International Conference on Intelligent User Interfaces, IUI 2025

作者： Chen, Yu Verbert, Katrien Gerling, Kathrin Vanden Abeele, Marie-Elena Vanden Abeele, Vero Department of Computer Sciences Ku Leuven Leuven Belgium Human-Computer Interaction and Accessibility Karlsruhe Institute of Technology Karlsruhe Germany Department of Geriatrics Jessa Hospital Hasselt Belgium

ISBN: (纸本)9798400713064

This paper explores the adoption of a clinical decision support system (cDSS) utilizing game-based digital biomarkers for diagnosing mild cognitive impairment (MCI). Specifically, it investigates how different explanation methods, with a focus on data-centric explanations, impact perceived ease-of-use, perceived usefulness, and trust among healthcare professionals (HCPs). Through a qualitative study with 12 HCPs, we assess their interactions with an explainable AI (XAI)-enriched cDSS. The findings indicate that HCPs are open to adopting XAI-enriched cDSS to communicate the outcomes of game-based digital biomarkers. HCPs preferred to receive key diagnostic information in an easily digestible format. Both local explanations of intra-personal evolutionary data and global overview of normative data were found to be valuable for interpreting digital biomarkers. HCPs tended to trust the machine learning algorithms as a black box, but they considered the dataset used for training the model and the outcome prediction to be crucial. Therefore, presenting the uncertainty alongside the prediction was deemed important. These insights underscore the importance of designing cDSS tools that foster trust through clear, actionable explanations, paving the way for improved decision-making in clinical contexts. © 2025 Copyright held by the owner/author(s).

关键词： Electronic health record

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Trans4Trans: Efficient transformer for transparent object and semantic scene segmentation in real-world navigation assistance

arXiv

引用

arXiv 2021年

作者： Zhang, Jiaming Yang, Kailun Constantinescu, Angela Peng, Kunyu Müller, Karin Stiefelhagen, Rainer Computer Vision for Human-Computer Interaction Lab Center for Digital Accessibility and Assistive Technology Karlsruhe Institute of Technology Germany

Transparent objects, such as glass walls and doors, constitute architectural obstacles hindering the mobility of people with low vision or blindness. For instance, the open space behind glass doors is inaccessible, unless it is correctly perceived and interacted with. However, traditional assistive technologies rarely cover the segmentation of these safety-critical transparent objects. In this paper, we build a wearable system with a novel dualhead Transformer for Transparency (Trans4Trans) perception model, which can segment general- and transparent objects. The two dense segmentation results are further combined with depth information in the system to help users navigate safely and assist them to negotiate transparent *** propose a lightweight Transformer Parsing Module (TPM) to perform multi-scale feature interpretation in the transformer-based decoder. Benefiting from TPM, the double decoders can perform joint learning from corresponding datasets to pursue robustness, meanwhile maintain efficiency on a portable GPU, with negligible calculation increase. The entire Trans4Trans model is constructed in a symmetrical encoder-decoder architecture, which outperforms state-of-the-art methods on the test sets of Stanford2D3D and Trans10K-v2 datasets, obtaining mIoU of 45:13% and 75:14%, respectively. Through a user study and various pre-tests conducted in indoor and outdoor scenes, the usability and reliability of our assistive system have been extensively verified. Meanwhile, the Tran4Trans model has outstanding performances on driving scene datasets. On Cityscapes, ACDC, and DADA-seg datasets corresponding to common environments, adverse weather, and traffic accident scenarios, mIoU scores of 81:5%, 76:3%, and 39:2% are obtained, demonstrating its high efficiency and robustness for real-world transportation applications. Copyright © 2021, The Authors. All rights reserved.

关键词： computer vision

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Beyond web content accessibility guidelines. Expert accessibility reviews 2016

Beyond web content accessibility guidelines. Expert accessib...

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7th International Conference on Software Development and Technologies for Enhancing accessibility and Fighting Info-Exclusion, DSAI 2016

作者： Calvo, Rocio Seyedarabi, Faezeh Savva, Andreas AbilityNet Department of Accessibility Services LondonEC1V 2PT United Kingdom Human-Computer Interaction Research Group University of York Department of Computer Science YorkYO10 5GH United Kingdom

ISBN: (纸本)9781450347488

Despite the existence of web accessibility guidelines - e.g. Web Content accessibility Guidelines - to help developers and designers to create more accessible websites, many websites are still not accessible. Studies showed that guidelines do not cover all the problems encounter by users with disabilities. This study investigates the problems found by seven accessibility experts in 62 accessibility evaluation reviews of mobile and desktop websites as well as mobile applications. Each evaluation conducted an accessibility review using Web Content accessibility Guidelines 2.0 AA. In addition, experts highlighted potential issues which were not covered by these guidelines but could be potential issues encountered by people with disabilities. The study depicts those issues that were raised by experts during those audits but were not covered by the WCAG 2.0 guidelines. Finally, the study provides additional knowledge into potential problems as identified by experts and recommends techniques that developers and designers can use to create more accessible websites. © 2016 ACM.

关键词： Websites

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