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We have also analyzed system sensitivity showing the impact of the number of evidences and their evidence degrees on the system performance and accuracy.
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Figure 5 Evidence degree impact.
(b) The impact of evidence degree on false positive rate.
(a) The impact of evidence degree on detection rate.
Our current implementation of SeeBot has the average evidence degree 23 among all defined evidences.
We use a parameter Evidence Degree (or ED) to indicate the number of associated symptoms.
However, the improvement due to increasing evidences and symptoms becomes much slow after certain thresholds as the total evidences |E1|=8, |E2|=4 and the average evidence degree 15.
The proposed results put in evidence some degrees of freedom that can be used for design purposes.
Using the belief structure associated with evidence theory, degrees of belief are numerically specified for subsets of a model set.
However, significant inconsistency was observed between direct and indirect evidence (χ=80.74, degrees of freedom=51, p=0.005, heterogeneity variance=0.01).
These new methods allowed for the publication of recommendations for preventive interventions according to a scale based on the levels of scientific evidence and degrees of recommendation.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com