AI in orthodontic treatment planning: a systematic review comparing learning approaches
Martin Baxmann, Márton Zsoldos, Krisztina Kárpáti · 2026
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Description
Martin Baxmann, Márton Zsoldos, and Krisztina Kárpáti published a 2026 review of AI in orthodontic planning. Orthodontists must decide on tooth removal, jaw class, and treatment type. Their calls often differ from each other. The team searched six databases to October 2025. They kept studies that used real patient data and rated each study's bias risk.
Nineteen studies qualified for the review. Most tested learning models for removal and jaw class calls. Reported accuracy often passed 80 percent against expert calls. Rule-based systems showed their reasoning more clearly. Data-driven models often scored higher. Bias was mostly moderate to serious, driven by backward-looking designs. The team urges tests in new clinics before real use.
Catalog record
| CREATOR | Martin Baxmann, Márton Zsoldos, Krisztina Kárpáti |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 59393 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |