This study aimed to evaluate the usage of the Checklist for Artificial Intelligence in Medical Imaging (CLAIM), a well-known and widely adopted checklist in the radiological community, for self-reporting through a systematic analysis of its citations. The authors used three databases (Google Scholar, Web of Science, and Scopus) and identified nearly 400 unique citations across 118 papers, of which only 10% provided proof of self-reported CLAIM checklist and over half mentioned some adherence to CLAIM without providing proof in the form of a checklist.
The results showed that only a small amount of the publications used CLAIM as a checklist. Thus, the authors hope that their findings can motivate the artificial intelligence community how important proper self-reporting is and that researchers, journals, editors, and reviewers become more proactive in ensuring the appropriate usage of checklists.
Key points
- Of 118 eligible papers, only 12 (10%) followed the CLAIM checklist for self-reporting with proof (i.e., filled-out checklist). More than half (70; 59%) only mentioned some kind of adherence without providing any proof.
- Overall, claims on 57 to 93% of the items were valid in item-by-item confirmation analysis, with a mean and standard deviation of 81% and 10%, respectively.
- Even with the checklist proof, the items declared may contain errors and should be approached cautiously.
Authors: Burak Kocak, Ali Keles & Tugba Akinci D’Antonoli
