A5005562426- Big Data and Business Intelligence
- Semantic Web and Ontologies
- Business Process Modeling and Analysis
- Machine Learning in Healthcare
- Hospital Admissions and Outcomes
- Artificial Intelligence in Healthcare and Education
- Information Systems Theories and Implementation
- Intelligence, Security, War Strategy
- Service-Oriented Architecture and Web Services
- Persona Design and Applications
- Ethics and Social Impacts of AI
- Healthcare Operations and Scheduling Optimization
- Information and Cyber Security
Roskilde University
2023-2024
Artificial intelligence techniques, including machine learning (ML), have shown remarkable test results over the past decade but struggled with transfer to practical application. The present study applies action research investigate this last stage of a project implement an ML algorithm for predicting no-shows at Danish hospital. We approach implementation no-show as innovation process and identify 14 tactics that were employed provide necessary stage. span three analytic levels –...
In its promise to contribute considerable cost savings and improved patient care through efficient analysis of the tremendous amount data stored in electronic health records (EHR), there is currently a strong push for proliferation artificial intelligence (AI) health-care. We identify, study AI being used predict no-show's, that gain full potential lies need balance introduction with proper focus on patients clinicians' interests. call Participatory Design (PD) approach understand...
Patients who do not show up for scheduled appointments are a considerable cost and concern in healthcare. In this study, we predict patient no-shows outpatient surgery at the endoscopy ward of hospital Denmark. The predictions made by training machine leaning (ML) models on available data, which have been recorded purposes other than ML, doing situated work setting to understand local data practices fine-tune models. best performing model (XGBoost with oversampling) predicts sensitivity =...