Determining Thresholds for Computer‐Aided Detection for Silicosis—An Analytic Approach

In applying CAD to silicosis, users need to establish the use case, their preference for the sensitivity/specificity trade-off, and the silicosis definition, as well as considering the effect of disease prevalence. System developers need to take inter-reader variation in validation exercises into account and present this information transparently. A two-threshold model has potential utility in situations of high screening volume where there is a significant cost associated with referral for confirmation of diagnosis.

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Publication Details

Journal
American Journal of Industrial Medicine
Published
2025-04-06
DOI
https://doi.org/10.1002/ajim.23720
Citations
2
Primary Topic
COVID-19 diagnosis using AI
Type
article
Field-Weighted Citation Impact
2.72
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article

Determining Thresholds for Computer‐Aided Detection for Silicosis—An Analytic Approach

Barry Kistnasamy, Stephen Barker, Rodney Ehrlich, Annalee Yassi et al.
2 citations
American Journal of Industrial Medicine
COVID-19 diagnosis using AI
2.72
article

Determining Thresholds for Computer‐Aided Detection for Silicosis—An Analytic Approach

Barry Kistnasamy, Stephen Barker, Rodney Ehrlich, Annalee Yassi, Jerry Spiegel
article en
2 citations

Abstract

In applying CAD to silicosis, users need to establish the use case, their preference for the sensitivity/specificity trade-off, and the silicosis definition, as well as considering the effect of disease prevalence. System developers need to take inter-reader variation in validation exercises into account and present this information transparently. A two-threshold model has potential utility in situations of high screening volume where there is a significant cost associated with referral for confirmation of diagnosis.

American Journal of Industrial MedicineVol. 68(5)
University of British Columbia (CA), University of Cape Town (ZA)
Quality Education
Openalex Percentile: Top 11%
COVID-19 diagnosis using AI
2.72
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