首页|University of Edinburgh Reports Findings in Machine Learning (A review on statistical and machine learning competing risks methods)
University of Edinburgh Reports Findings in Machine Learning (A review on statistical and machine learning competing risks methods)
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New research on Machine Learning is the subject of a report. According to news reporting from Edinburgh, United Kingdom, by NewsRx journalists, research stated, "When modeling competing risks (CR) survival data, several techniques have been proposed in both the statistical and machine learning literature. State-of-the-art methods have extended classical approaches with more flexible assumptions that can improve predictive performance, allow high-dimensional data and missing values, among others." The news correspondents obtained a quote from the research from the University of Edinburgh, "Despite this, modern approaches have not been widely employed in applied settings. This article aims to aid the uptake of such methods by providing a condensed compendium of CR survival methods with a unified notation and interpretation across approaches. We highlight available software and, when possible, demonstrate their usage via reproducible R vignettes." According to the news reporters, the research concluded: "Moreover, we discuss two major concerns that can affect benchmark studies in this context: the choice of performance metrics and reproducibility." This research has been peer-reviewed.
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