Evaluation of the diagnostic reliability of an AI prototype in detecting clinical features from dental photographs—original research
Saif Abdelaziz, Islam Yasser, Mazen Amgad, Mutaz Al Qudah, Rohit Kunnath Menon · 2026
Read Evaluation of the diagnostic reliability of an AI prototype in detecting clinical features from dental photographs—original research by Saif Abdelaziz, Islam Yasser, Mazen Amgad, Mutaz Al Qudah, Rohit Kunnath Menon (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13194533.txt.
Description
Saif Abdelaziz and four co-authors tested an AI prototype that reads dental photos in a 2026 paper. Software that spots disease signs in mouth photographs could speed screening, but its reliability must be proven first. The team compared the prototype against examiners' findings in 34 patients at a university dental clinic in Ajman.
Across 306 standard photos, the software hunted six features, from decay and tartar to bleeding and staining. It was best at ruling disease out: its negative calls were right over 99 percent of the time for bleeding and retained roots. Its hit rate was weakest for staining, catching only about a quarter of cases. The authors call it a useful exclusion tool that still misses too much to stand alone.
Catalog record
| CREATOR | Saif Abdelaziz, Islam Yasser, Mazen Amgad, Mutaz Al Qudah, Rohit Kunnath Menon |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 36 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |