[HTML][HTML] Understanding the factors influencing acceptability of AI in medical imaging domains among healthcare professionals: A sco** review
Background Artificial intelligence (AI) technology has the potential to transform medical
practice within the medical imaging industry and materially improve productivity and patient …
practice within the medical imaging industry and materially improve productivity and patient …
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 …
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 …
Investigating the heart pump implant decision process: opportunities for decision support tools to help
Clinical decision support tools (DSTs) are computational systems that aid healthcare
decision-making. While effective in labs, almost all these systems failed when they moved …
decision-making. While effective in labs, almost all these systems failed when they moved …
[PDF][PDF] The role of design in creating machine-learning-enhanced user experience
Q Yang - 2017 AAAI spring symposium series, 2017 - cdn.aaai.org
Abstract Machine learning (ML) applications that directly interface with everyday users are
now increasingly pervasive and powerful. However, user experience (UX) practitioners are …
now increasingly pervasive and powerful. However, user experience (UX) practitioners are …
User-centred design of a clinical decision support system for palliative care: Insights from healthcare professionals
V Blanes-Selva, S Asensio-Cuesta… - Digital …, 2023 - journals.sagepub.com
Objective: Although clinical decision support systems (CDSS) have many benefits for clinical
practice, they also have several barriers to their acceptance by professionals. Our objective …
practice, they also have several barriers to their acceptance by professionals. Our objective …
[PDF][PDF] Technical Feasibility, Financial Viability, and Clinician Acceptance: On the Many Challenges to AI in Clinical Practice.
Artificial intelligence (AI) applications in healthcare offer the promise of improved decision
making for clinicians, and better healthcare outcomes for patients. While technical AI …
making for clinicians, and better healthcare outcomes for patients. While technical AI …
Profiling artificial intelligence as a material for user experience design
Q Yang - 2020 - search.proquest.com
From predictive medicine to autonomous driving, advances in Artificial Intelligence (AI)
promise to improve people's lives and improve society. As systems that utilize these …
promise to improve people's lives and improve society. As systems that utilize these …
How Much Decision Power Should (A) I Have?: Investigating Patients' Preferences Towards AI Autonomy in Healthcare Decision Making
Despite the growing potential of artificial intelligence (AI) in improving clinical decision
making, patients' perspectives on the use of AI for their care decision making are …
making, patients' perspectives on the use of AI for their care decision making are …
[HTML][HTML] Prediction of Bladder Cancer Treatment Side Effects Using an Ontology-Based Reasoning for Enhanced Patient Health Safety
Predicting potential cancer treatment side effects at time of prescription could decrease
potential health risks and achieve better patient satisfaction. This paper presents a new …
potential health risks and achieve better patient satisfaction. This paper presents a new …