Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such “big data,” attempts have focused on large sampling algorithms that model individual data points. However, since these algorithms sample the entire dataset millions of times, their theoretically very high level of precision comes at a prohibitive computational cost and therefore remains unattainable. To overcome this, scientists previously developed approaches that sacrifice accuracy for speed.
This article was originally published on MedicalXpress.com
