Data Quality for the Application of Artificial Intelligence in Medical and Dental Diagnostic Imaging: A Scoping Review and Checklists for Critical Appraisal and Metadata Reporting

The adoption of artificial intelligence, in particular machine learning, has seen a rise in the field of medicine and dentistry. Although artificial intelligence has shown potential in guiding medical and dental diagnosis of different radiographic or non-radiographic imaging modalities, the confidence in its utilization warrants further development and utilization of good quality training data. Thus, the aim of this scoping review is to to explore and map out key data quality characteristics for AI applications in medical and dental diagnostic imaging, and to develop critical appraisal checklists and metadata reporting checklists for data users, researchers and authors.