output
20082026
most citedExplainable artificial intelligence (XAI) in deep learning-based medical image analysis

1.3k citations

Showing 2021 · stat.MEShow all

6 papers · 2 filters

stat.ME2021★ 55 cited

Bayesian Model-Averaged Meta-Analysis in Medicine

František Bartoš, Quentin F. Gronau, Bram Timmers +3

We outline a Bayesian model-averaged meta-analysis for standardized mean differences in order to quantify evidence for both treatment effectiveness and across-study heterogenei…

stat.ME2021★ 75 cited

A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint

J Hoogland, J IntHout, M Belias +6

Randomized trials typically estimate average relative treatment effects, but decisions on the benefit of a treatment are possibly better informed by more individualized predictions…

stat.ME2021★ 8 cited

Misuse of the sign test in narrative synthesis of evidence

Stavros Nikolakopoulos

In narrative synthesis of evidence, it can be the case that the only quantitative measures available concerning the efficacy of an intervention is the direction of the effect, i.e.…

stat.ME2021★ 8 cited

Statistical Integration of Heterogeneous Data with PO2PLS

Said el Bouhaddani, Hae-Won Uh, Geurt Jongbloed +1

The availability of multi-omics data has revolutionized the life sciences by creating avenues for integrated system-level approaches. Data integration links the information across…

stat.ME2021★ 13 cited

Extending the Mann-Kendall test to allow for measurement uncertainty

Stavros Nikolakopoulos, Eric Cator, Mart P. Janssen

The Mann-Kendall test for trend has gained a lot of attention in a range of disciplines, especially in the environmental sciences. One of the drawbacks of the Mann-Kendall test whe…

stat.ME2021★ 1 cited

Comparing methods addressing multi-collinearity when developing prediction models

Artuur M. Leeuwenberg, Maarten van Smeden, Johannes A. Langendijk +5

Clinical prediction models are developed widely across medical disciplines. When predictors in such models are highly collinear, unexpected or spurious predictor-outcome associatio…