28 citations · 28 across the 1 of their papers we have counts for
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stat.AP2020
The importance of transparency and reproducibility in artificial intelligence research
Benjamin Haibe-Kains, George Alexandru Adam, Ahmed Hosny +17
In their study, McKinney et al. showed the high potential of artificial intelligence for breast cancer screening. However, the lack of detailed methods and computer code undermines…
stat.AP2015★ 28 cited
Bayesian nonparametric cross-study validation of prediction methods
Lorenzo Trippa, Levi Waldron, Curtis Huttenhower +1
We consider comparisons of statistical learning algorithms using multiple data sets, via leave-one-in cross-study validation: each of the algorithms is trained on one data set; the…