Artificial Intelligence‐Assisted Treatment Planning in an Interdisciplinary Rehabilitation in the Esthetic Zone
Year: 2025
Type: article
Study design: Case Report
Abstract: OBJECTIVES: This case report elucidates the application of an integrated digital workflow in which diagnosis, planning, and execution were enhanced by artificial intelligence (AI), enabling an assertive interdisciplinary esthetic-functional rehabilitation. With AI-powered software, the sequence from orthodontic treatment to the final rehabilitation achieved high predictability, addressing patient's chief complaints. CLINICAL CONSIDERATIONS: A patient presented with a missing maxillary left central incisor (tooth 11) and dissatisfaction with a removable partial denture. Clinical examination revealed a gummy smile, a deviated midline, and a disproportionate mesiodistal space relative to the midline. Initial documentation included photographs, intraoral scanning, and cone-beam computed tomography of the maxilla. These data were integrated into a digital planning software to create an interdisciplinary plan. This workflow included prosthetically guided orthodontic treatment with aligners, a motivational mockup, guided implant surgery, peri-implant soft tissue management, and final prosthetic rehabilitation using a CAD/CAM approach. CONCLUSIONS: This digital workflow enhanced communication among the multidisciplinary team and with the patient, ensuring highly predictable esthetic and functional outcomes. CLINICAL SIGNIFICANCE: Comprehensive digital workflows improve diagnostic accuracy, streamline planning with AI, and facilitate patient understanding. This approach increases patient satisfaction, supports interdisciplinary collaboration, and promotes treatment adherence.
DOI: 10.1111/jerd.70034
Authors: F. J. P. O. Fonseca, B. B. R. Matias, P. Pacheco, C. S. A. S. Muraoka, E. V. F. Silva, N. Sesma
Institutions: Faculdade São Leopoldo Mandic, Universidade de São Paulo
Language: English
Subfield: Orthodontics
Field: Dentistry
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,030
Award: G3690646728
OpenAlex ID: W4414390876
