Data clustering to select clinically-relevant test cases for algorithm benchmarking and characterization.

CONCLUSIONS: The framework successfully clustered workflow outputs and identified five test cases representative of clinically relevant algorithm discrepancies. This approach may improve the allocation of resources during the benchmarking and characterization process and the applicability of results to clinical data. PMID: 31962297 [PubMed - as supplied by publisher]

https://www.ncbi.nlm.nih.gov/pubmed/31962297?dopt=Abstract

Source: Physics in Medicine and Biology - January 20, 2020 Category: Physics Authors: Weppler S, Schinkel C, Kirkby C, Smith WL Tags: Phys Med Biol Source Type: research