Abstract
New research on artificial intelligence is the subject of a new report. According to news reporting originating from the University of Sydney by NewsRx correspondents, research stated, “To investigate the management of imaging errors from panoramic radiography (PAN) datasets used in the development of machine learning (ML) models. This systematic literature followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and used three databases.” Our news editors obtained a quote from the research from University of Sydney: “Keywords were selected from relevant literature. Eligibility criteria: PAN studies that used ML models and mentioned image quality concerns. Out of 400 articles, 41 papers satisfied the inclusion criteria. All the studies used ML models, with 35 papers using deep learning (DL) models. PAN quality assessment was approached in 3 ways: acknowledgement and acceptance of imaging errors in the ML model, removal of low-quality radiographs from the dataset before building the model, and application of image enhancement methods prior to model development. The criteria for determining PAN image quality varied widely across studies and were prone to bias.”
NETL
NSTL
British Inst Radiology