The goal of this study is to explore the different attitudes and preconditions of potential end-users (doctors \& physicians in training) required to achieve successful clinical implementation of models based on artificial intelligence (i.e. both machine learning and knowledge-driven techniques) as clinical decision support software.
Age range
18 Years
Sex
ALL
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
Baseline attitudes towards artificial intelligence and big data in medicine
Timeframe: baseline
Identify subdomains of the antimicrobial stewardship cycle with potential for AI/Big data application
Timeframe: through study completion, an average of 1 year
Identify perceived potential benefits and harms when applying AI in the antimicrobial stewardship cycle.
Timeframe: through study completion, an average of 1 year
Identify prerequisites that need to be fulfilled when AI/Big data based clinical decision support systems are used bedside from the viewpoint of the participants.
Timeframe: through study completion, an average of 1 year