BIAS: Transparent reporting of biomedical image analysis challenges
Lena Maier-Hein, Annika Reinke, Michal Kozubek, Anne L. Martel, Tal, Arbel, Matthias Eisenmann, Allan Hanbuary, Pierre Jannin, Henning M\"uller,, Sinan Onogur, Julio Saez-Rodriguez, Bram van Ginneken, Annette, Kopp-Schneider, Bennett Landman

TL;DR
The paper introduces the BIAS initiative, providing guidelines and a checklist to improve transparency, reproducibility, and interpretability in reporting biomedical image analysis challenges.
Contribution
It develops a standardized reporting checklist to enhance clarity and reproducibility of biomedical image analysis challenge results.
Findings
Development of the BIAS reporting checklist
Improved transparency in challenge reporting
Facilitation of review and interpretation processes
Abstract
The number of biomedical image analysis challenges organized per year is steadily increasing. These international competitions have the purpose of benchmarking algorithms on common data sets, typically to identify the best method for a given problem. Recent research, however, revealed that common practice related to challenge reporting does not allow for adequate interpretation and reproducibility of results. To address the discrepancy between the impact of challenges and the quality (control), the Biomedical I mage Analysis ChallengeS (BIAS) initiative developed a set of recommendations for the reporting of challenges. The BIAS statement aims to improve the transparency of the reporting of a biomedical image analysis challenge regardless of field of application, image modality or task category assessed. This article describes how the BIAS statement was developed and presents a…
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Taxonomy
MethodsInterpretability
