Emerging paradigms of cognition in medical decision-making
By Vimla L. Patel, D. Kaufman, J. Arocha. Journal of Biomedical Informatics, 2002
355 citations recorded by the source corpus.
Subfields: Economics and Econometrics, General Decision Sciences, General Health Professions
View Paper: https://www.semanticscholar.org/paper/01f2324f04c42177bf525c72b4e8b788fe7635f2
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
In General Decision Sciences
In General Health Professions
- Trevor Jamieson
- James Shaw
- Frank Rudzicz
- Avi Goldfarb
- L. Millward
- Geraldine Fitzpatrick
- Rowanne Fleck
- Gunnar Ellingsen
Citations in the corpus
- Naturalistic Decision Making and Organizations: Reviewing Pragmatic Science (2006, background): “Indeed, the imperative to make accurate decisions is a very real one given growing research highlighting that ‘physicians’ decisions too often … lead to adverse consequences for a patient’ (Patel et al. 2002: 52).”
- A unified foundation for business analytics (2014, background): “While decision making is certainly a key facet of business, a manager is also concerned with solvingmore than decision problems.”
- Cognitive Biases and Heuristics in Medical Decision Making (2015, background): “’’ Real-world clinical decision making is also mediated by technology and teamwork.(7) Thus, ‘‘one can argue that traditional and naturalistic decision making researchers are in fact studying markedly different phenomena.”
- MAHI: investigation of social scaffolding for reflective thinking in diabetes management (2008, background): “Much of the work in supporting decision-making for analysts tends to be informed by research in decisionmaking [22] that has a clearly defined normative character and presupposes an existence of an “optimal” decision in majority of situations.”
- Artificial Intelligence and the Implementation Challenge (2019, background): “Clinical decision making is a complex process involving the integration of a variety of data sources, incorporating both tacit and explicit modes of intelligence [34-36].”