“…In other words, institutions without access to established experts may still be able to produce high-quality data for algorithmic development. Notably, recent literature suggests that DL models trained on consensus contours can be influenced by biased annotations, 11 underscoring the importance of judicious application of these consensus methods. Figure 2 Consensus from a limited number of nonexpert contours can approximate expert reference standard benchmarks.…”
“…In other words, institutions without access to established experts may still be able to produce high-quality data for algorithmic development. Notably, recent literature suggests that DL models trained on consensus contours can be influenced by biased annotations, 11 underscoring the importance of judicious application of these consensus methods. Figure 2 Consensus from a limited number of nonexpert contours can approximate expert reference standard benchmarks.…”
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