Clinical Decision Support Systems: Theory and Practice

By Eta S. Berner, K. Hannah, M. Ball. 1998

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Emma Beede
2. E. Baylor
3. Daniel C. Baumgart
4. Fred Hersch
5. A. Iurchenko
6. Paisan Ruamviboonsuk
7. Laura M. Vardoulakis
8. Lauren Wilcox

Citations in the corpus

• A Human-Centered Evaluation of a Deep Learning System Deployed in Clinics for the Detection of Diabetic Retinopathy (2020, background): “Past work on systems using artificial intelligence, such as computer-aided detection (CAD) [10] or Decision Support Tools (DSTs) [4] has highlighted several obstacles in going from research and development environments to hospital or clinical settings.”
• An overview of clinical decision support systems: benefits, risks, and strategies for success (2020, methodology): “There are many other examples including computerized ECG analysis, automated arterial blood gas interpretation, protein electrophoresis reports, and CDSS for blood cell counting.(46)”