AI-driven prediction of treatment outcome in aligner therapy: A pilot study
Clear aligner therapy is popular, but predicting whether patients will need refinement remains difficult. In this pilot study, 30 adults undergoing aligner therapy were assessed with an AI model trained on 2000 historical cases to forecast outcomes. The model predicted treatment completion without refinement with 70% accuracy, showing 75% sensitivity and 66.7% specificity. These findings indicate that AI can moderately predict refinement needs and may support personalized treatment planning in orthodontics.
Authors
- Rahul Tiwari (ORCID: https://orcid.org/0000-0003-4156-776X)
- Ajay K. Kubavat (ORCID: https://orcid.org/0000-0003-2099-9715)
- Preetham Ravuri
- Anil Managutti (ORCID: https://orcid.org/0000-0003-4958-8346)
- Bhagyalakshmi Avinash (ORCID: https://orcid.org/0000-0003-4131-8106)
- Leela Venkata Soujanya Nallamilli
- Faisal Ansari
- Udayini Monica M
Institutions
- Alfaisal University (SA)
- Manubhai Patel Dental College and Hospital (IN)
- Sankalchand Patel University (IN)
- JSS Dental College and Hospital (IN)
- Kamineni Institute of Dental Sciences (IN)
Publication Details
- Journal
- Bioinformation
- Published
- 2025-09-30
- DOI
- https://doi.org/10.6026/973206300213404
- Primary Topic
- Biomedical and Engineering Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00