2 citations · 2 across the 2 of their papers we have counts for
3 papers
Implementation Guidelines for Data Quality Metrics
Philipp Jung, Katinka Becker, Felix Biessmann +4
Despite decades of data quality (DQ) research, a gap remains between DQ dimensions, such as accuracy or completeness, which the literature defines in textual form, and DQ tools, wh…
Metric Hub: A metric library and practical selection workflow for use-case-driven data quality assessment in medical AI
Katinka Becker, Maximilian P. Oppelt, Tobias S. Zech +19
Machine learning (ML) in medicine has transitioned from research to concrete applications aimed at supporting several medical purposes like therapy selection, monitoring and treatm…
The METRIC-framework for assessing data quality for trustworthy AI in medicine: a systematic review
Daniel Schwabe, Katinka Becker, Martin Seyferth +2
The adoption of machine learning (ML) and, more specifically, deep learning (DL) applications into all major areas of our lives is underway. The development of trustworthy AI is es…