What Your Radiologist Might be Missing: Using Machine Learning to Identify Mislabeled Instances of X-ray Images

dc.contributor.author Rädsch, Tim
dc.contributor.author Eckhardt, Sven
dc.contributor.author Leiser, Florian
dc.contributor.author Pandl, Konstantin D.
dc.contributor.author Thiebes, Scott
dc.contributor.author Sunyaev, Ali
dc.date.accessioned 2020-12-24T19:14:37Z
dc.date.available 2020-12-24T19:14:37Z
dc.date.issued 2021-01-05
dc.description.abstract Label quality is an important and common problem in contemporary supervised machine learning research. Mislabeled instances in a data set might not only impact the performance of machine learning models negatively but also make it more difficult to explain, and thus trust, the predictions of those models. While extant research has especially focused on the ex-ante improvement of label quality by proposing improvements to the labeling process, more recent research has started to investigate the use of machine learning-based approaches to identify mislabeled instances in training data sets automatically. In this study, we propose a two-staged pipeline for the automatic detection of potentially mislabeled instances in a large medical data set. Our results show that our pipeline successfully detects mislabeled instances, helping us to identify 7.4% of mislabeled instances of Cardiomegaly in the data set. With our research, we contribute to ongoing efforts regarding data quality in machine learning.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2021.157
dc.identifier.isbn 978-0-9981331-4-0
dc.identifier.uri http://hdl.handle.net/10125/70769
dc.language.iso English
dc.relation.ispartof Proceedings of the 54th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Explainable Artificial Intelligence (XAI)
dc.title What Your Radiologist Might be Missing: Using Machine Learning to Identify Mislabeled Instances of X-ray Images
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