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

Authors: Kaijing Mao, Jason Chi-Kit Ku
Cited by: 0

Abstract

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 summarize current evidence and construct an evidence-based framework to optimize data quality of artificial intelligence datasets in the field of medical and dental diagnostic imaging.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Dental Radiography and Imaging Artificial Intelligence in Healthcare

Publication details

Journal / source
OSF Preprints (OSF Preprints)
Publication date
4 February 2026
Document type
Preprint