HIGHLIGHTS
- who: Matthias Neumair from the Department of Life Sciences, Technical University of Munich, Freising, Germany have published the article: Accommodating heterogeneous missing data patterns for prostate cancer risk prediction, in the Journal: (JOURNAL)
- what: The aim of this study was to construct a clinically significant prostate cancer risk tool that would optimize the use of data from heterogeneous cohorts with varying missing data patterns and allow end-users of the tools access even when missing some risk factors. The study was based on risk factor and outcome data collected from January 2006 to December 2019 . . .
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