Designing AI for trust and collaboration in time-constrained medical decisions: a sociotechnical lens
Major depressive disorder is a debilitating disease affecting 264 million people worldwide.
While many antidepressant medications are available, few clinical guidelines support …
While many antidepressant medications are available, few clinical guidelines support …
Healthcare AI treatment decision support: Design principles to enhance clinician adoption and trust
ER Burgess, I Jankovic, M Austin, N Cai… - Proceedings of the …, 2023 - dl.acm.org
Artificial intelligence (AI) supported clinical decision support (CDS) technologies can parse
vast quantities of patient data into meaningful insights for healthcare providers. Much work is …
vast quantities of patient data into meaningful insights for healthcare providers. Much work is …
Harnessing biomedical literature to calibrate clinicians' trust in AI decision support systems
Clinical decision support tools (DSTs), powered by Artificial Intelligence (AI), promise to
improve clinicians' diagnostic and treatment decision-making. However, no AI model is …
improve clinicians' diagnostic and treatment decision-making. However, no AI model is …
Unremarkable AI: Fitting intelligent decision support into critical, clinical decision-making processes
Clinical decision support tools (DST) promise improved healthcare outcomes by offering
data-driven insights. While effective in lab settings, almost all DSTs have failed in practice …
data-driven insights. While effective in lab settings, almost all DSTs have failed in practice …
Co-design of human-centered, explainable AI for clinical decision support
eXplainable AI (XAI) involves two intertwined but separate challenges: the development of
techniques to extract explanations from black-box AI models and the way such explanations …
techniques to extract explanations from black-box AI models and the way such explanations …
How incorporating feedback mechanisms in a DSS affects DSS evaluations
U Kayande, A De Bruyn, GL Lilien… - Information Systems …, 2009 - pubsonline.informs.org
Model-based decision support systems (DSS) improve performance in many contexts that
are data-rich, uncertain, and require repetitive decisions. But such DSS are often not …
are data-rich, uncertain, and require repetitive decisions. But such DSS are often not …
Designing theory-driven user-centric explainable AI
From healthcare to criminal justice, artificial intelligence (AI) is increasingly supporting high-
consequence human decisions. This has spurred the field of explainable AI (XAI). This …
consequence human decisions. This has spurred the field of explainable AI (XAI). This …
Assessing the value of ChatGPT for clinical decision support optimization
ABSTRACT Objective To determine if ChatGPT can generate useful suggestions for
improving clinical decision support (CDS) logic and to assess noninferiority compared to …
improving clinical decision support (CDS) logic and to assess noninferiority compared to …
[HTML][HTML] How the different explanation classes impact trust calibration: The case of clinical decision support systems
Abstract Machine learning has made rapid advances in safety-critical applications, such as
traffic control, finance, and healthcare. With the criticality of decisions they support and the …
traffic control, finance, and healthcare. With the criticality of decisions they support and the …
" The human body is a black box" supporting clinical decision-making with deep learning
Machine learning technologies are increasingly developed for use in healthcare. While
research communities have focused on creating state-of-the-art models, there has been less …
research communities have focused on creating state-of-the-art models, there has been less …