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| Hauptseite > Publikationsdatenbank > 10 years of reproducibility in biomedical research: howcan we achieve generalizability and fairness? |
| Hauptseite > Publikationsdatenbank > 10 years of reproducibility in biomedical research: howcan we achieve generalizability and fairness? |
| Conference Presentation (After Call) | FZJ-2023-05213 |
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2023
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Please use a persistent id in citations: doi:10.34734/FZJ-2023-05213
Abstract: 10 years ago, a series of publications pointed to the difficulty of reproducing scientific findings. Thisreproducibility crisis was a wake-up call for scientific communities to rethink how we practice andcommunicate research, and an important driver towards greater transparency and robust results. Ever since,biomedical imaging undertook various efforts to overcome reproducibility issues: From increasing samplesizes for higher statistical power, to data sharing and increased collaborations to acquire such samples, andpromoting detailed reporting practices and code sharing to ease computational reproducibility.But where are we standing with respect to reproducible biomedical imaging now? We discuss recentadvances and open questions, and focus on how the conversation has moved beyond efforts to reduce falsepositive findings to broader questions of generalizability and fairness. How does a finding observed in agiven group apply to the population at large? How does a finding obtained with one analysis vary whencomputed using another tool? How does a finding observed in a given group apply to subgroups of thatpopulation, in particular to less represented subgroups? How can open science help with the complexquestions of building fair algorithms and fairness in who participates in the process of science?
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