Reproducibility of artificial intelligence models in computed tomography of the head: a quantitative analysis.

ABSTRACT: When developing artificial intelligence (AI) software for applications in radiology, the underlying research must be transferable to other real-world problems. To verify to what degree this is true, we reviewed research on AI algorithms for computed tomography of the head. A systematic review was conducted according to the preferred reporting items for systematic reviews and meta-analyses. We identified 83 articles and analyzed them in terms of transparency of data and code, pre-processing, type of algorithm, architecture, hyperparameter, performance measure, and balancing of dataset in relation to epidemiology. We also classified all articles by their main functionality (classification, detection, segmentation, prediction, triage, image reconstruction, image registration, fusion of imagin

SUBMITTER: Gunzer F 

PROVIDER: S-EPMC9613832 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature