Studies have shown that father absence in opposite-gender couples has detrimental effects on children's wellbeing, net of selection bias. However, life course informed research suggests that the problem of selection bias may be more complex than curr...
Computational and mathematical methods in medicine
29312464
Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Sev...
Neural networks : the official journal of the International Neural Network Society
30978611
In this paper, we discuss the consensus problem of non-linear multi-agent systems where an impulsive protocol with event-based asynchronously sampled data is adopted. Systems that communicate by data asynchronously sampled in limited time intervals a...
Modern survey methods may be subject to non-observable bias, from various sources. Among online surveys, for example, selection bias is prevalent, due to the sampling mechanism commonly used, whereby participants self-select from a subgroup whose cha...
Radiographics : a review publication of the Radiological Society of North America, Inc
32976062
Machine learning (ML) algorithms have demonstrated high diagnostic accuracy in identifying and categorizing disease on radiologic images. Despite the results of initial research studies that report ML algorithm diagnostic accuracy similar to or excee...
The international journal of medical robotics + computer assisted surgery : MRCAS
33826236
BACKGROUND: Most comparisons of robot-assisted (RARC) versus open radical cystectomy (ORC) for urothelial carcinoma do not factor the inherent stage selection bias or surgical experience.
OBJECTIVE: Estimating the individualized treatment effect (ITE) from observational data is a challenging task due to selection bias, which results from the distributional discrepancy between different treatment groups caused by the dependence between...
International journal of environmental research and public health
37239641
Every research participant has their own personality characteristics. For example, older adults assisted by socially assistive robots (SAR) may have their own unique characteristics and may not be representative of the general population of older adu...
Supervised deep learning (DL) algorithms are highly dependent on training data for which human graders are assigned, for example, for optical coherence tomography (OCT) image annotation. Despite the tremendous success of DL, due to human judgment, th...