ArticleMDM policy & practice
Improving Diagnostic Efficiency with Frequency Double-Trees and Frequency Nets in Bayesian Reasoning.
Article in MDM policy & practice. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- The Use of Visualizations to Improve Bayesian Reasoning: A Literature Review.Vision (Basel, Switzerland) · 2023Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Highlights: Frequency double-trees and frequency nets help answer Bayesian tasks not only more accurately but also more quickly than the respective probability visualizations.In double-trees and net diagrams, the effect of the information format (probabilities v. natural frequencies) on performance is remarkably lower in this high-performing sample than that shown in previous studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.