# Artificial Intelligence‐Assisted Treatment Planning in an Interdisciplinary Rehabilitation in the Esthetic Zone

## TL;DR

This paper presents a case where AI-assisted digital workflows improved interdisciplinary dental rehabilitation, leading to better aesthetic and functional outcomes.

## Contribution

The novel use of AI in an integrated digital workflow for interdisciplinary dental rehabilitation is demonstrated.

## Key findings

- AI-assisted planning improved predictability in orthodontic and prosthetic treatment.
- Digital workflows enhanced communication among the dental team and with the patient.
- The approach increased patient satisfaction and treatment adherence.

## Abstract

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.

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.

This digital workflow enhanced communication among the multidisciplinary team and with the patient, ensuring highly predictable esthetic and functional outcomes.

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.