Web: http://arxiv.org/abs/2206.01653

Sept. 16, 2022, 1:15 a.m. | Lena Maier-Hein, Annika Reinke, Patrick Godau, Minu D. Tizabi, Evangelia Christodoulou, Ben Glocker, Fabian Isensee, Jens Kleesiek, Michal Kozubek, Ma

cs.CV updates on arXiv.org arxiv.org

Increasing evidence shows that flaws in machine learning (ML) algorithm
validation are an underestimated global problem. Particularly in automatic
biomedical image analysis, chosen performance metrics often do not reflect the
domain interest, thus failing to adequately measure scientific progress and
hindering translation of ML techniques into practice. To overcome this, a large
international expert consortium created Metrics Reloaded, a comprehensive
framework guiding researchers towards choosing metrics in a problem-aware
manner. Following the convergence of ML methodology across application domains,
Metrics …

analysis arxiv image metrics recommendations validation

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