Assessing the Impact of AI-Enhanced Diagnostic Tools on the Treatment Planning of Orthodontic Cases: An RCT

• Published in: Journal of pharmacy & bioallied science Vol. 16; no. Suppl 2; pp. S1798 - S1800
• Main Authors: Gaonkar, Prachi, Mohammed, Imad, Ribin, Mohammed, Kumar, D Chetan, Thomas, Pallavi A, Saini, Ruchi
• Format: Journal Article
• Language: English
• Published: India Medknow Publications & Media Pvt. Ltd 01.04.2024; Wolters Kluwer - Medknow; Wolters Kluwer Medknow Publications
• Subjects: 3d modeling; Accuracy; ai-enhanced diagnostics; cephalometric analysis; Original; Orthodontics; Patient satisfaction; randomized controlled trial; treatment planning; AI-enhanced diagnostics; treatment planning; orthodontics; 3D Modeling; cephalometric analysis; randomized controlled trial
• ISSN: 0976-4879; 0975-7406
• DOI: 10.4103/jpbs.jpbs_1147_23

Orthodontic treatment planning involves the precise assessment of dental and skeletal anomalies, which can be facilitated by AI-enhanced diagnostic tools. A total of 100 orthodontic cases were included in this RCT. Patients were randomly assigned to two groups: an AI-enhanced diagnostic group and a traditional diagnostic group. The AI-enhanced diagnostic group underwent orthodontic assessment with the aid of AI-powered software, which provided automated cephalometric analysis, 3D model evaluations, and treatment suggestions. The traditional diagnostic group received conventional diagnostic assessments by orthodontists. The primary outcome measures included treatment planning accuracy, treatment time, and patient satisfaction. Secondary outcomes included the number of appointments required and treatment cost. The AI-enhanced diagnostic group demonstrated a significantly higher accuracy in treatment planning compared to the traditional diagnostic group ( < 0.05). The AI group also required fewer appointments (mean ± SD: 10.2 ± 2.1 vs. 12.8 ± 3.4) and had a shorter treatment time (mean ± SD: 14.6 ± 3.2 months vs. 18.9 ± 4.5 months) ( < 0.001 for both comparisons). Additionally, patient satisfaction scores were higher in the AI group (mean ± SD: 9.2 ± 0.6 vs. 8.1 ± 0.8) ( < 0.001). However, the AI-enhanced diagnostic group had a slightly higher treatment cost. AI-enhanced diagnostic tools significantly enhance the accuracy of treatment planning in orthodontic cases, leading to reduced treatment time, fewer appointments, and increased patient satisfaction.