SeroTracker-RoB: a decision rule-based algorithm for reproducible risk of bias assessment of seroprevalence studies.

Niklas BobrovitzKim NoëlZihan LiChristian CaoGabriel DeveauxAnabel SelemonDavid A CliftonMercedes Yanes-LaneTingting YanRahul K Arora

Published in: Research synthesis methods (2023)

The SeroTracker-RoB decision-rule based algorithm was faster than non-algorithmic assessment with complete coverage and good reliability. This algorithm enabled rapid, transparent, and reproducible RoB evaluations of seroprevalence studies and may support evidence synthesis efforts during future disease outbreaks. This decision rule-based approach could be applied to other types of prevalence studies. This article is protected by copyright. All rights reserved.

Keyphrases

machine learning
deep learning
case control
decision making
risk factors
neural network
healthcare
current status
quantum dots
infectious diseases