ArticleDiagnostics (Basel, Switzerland)2021
A Software Tool for Calculating the Uncertainty of Diagnostic Accuracy Measures.
Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
4 citing papers in PubMed.
- A software tool for applying Bayes' theorem in medical diagnostics.BMC medical informatics and decision making · 2024Article
- Correction: Chatzimichail, T.; Hatjimihail, A.T. A Software Tool for Calculating the Uncertainty of Diagnostic Accuracy Measures.Diagnostics (Basel, Switzerland) · 2024Article
- A Software Tool for Estimating Uncertainty of Bayesian Posterior Probability for Disease.Diagnostics (Basel, Switzerland) · 2024Article
- A Bayesian Inference Based Computational Tool for Parametric and Nonparametric Medical Diagnosis.Diagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Screening and diagnostic tests are applied for the classification of people into diseased and non-diseased populations. Although diagnostic accuracy measures are used to evaluate the correctness of classification in clinical research and practice, there has been limited research on their uncertainty. The objective for this work was to develop a tool for calculating the uncertainty of diagnostic accuracy measures, as diagnostic accuracy is fundamental to clinical decision-making. For this reason, the freely available interactive program
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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.