Artificial Intelligence-Driven Prosthetic Rehabilitationin Partially Edentulous Patients: Long-Term Clinical Assessment of Implant-Supported Restorations

Lifestyle Artificial intelligence; Implant dentistry; Prosthodontics; Digital rehabilitation; Implant-supported restorations

Dr Deepika Kapoor1
Professor, Department of Pedodontics and
Preventive Dentistry
Luxmi Bai Institute of Dental Sciences and
Hospital, Patiala, Punjab
E-mail ID- [email protected]
Orcid ID: 0000-0002-3888-2593

Dr Mohammed Ismail B2
Professor , Periodontology And Implantology
Periodontology And Oral Implantology
Rajiv Gandhi University of Health Sciences,
Karnataka-560041, India, 583101
Email ID: [email protected]
OrcidID: 0009-0001-6362-0902

Dr Omkar Eswara Babu Danda3
Assistant professor, MDS
Conservative Dentistry and Endodontics
Department: Dentistry , Vijayawada, 520008
Dr Ntr University Of Health Sciences,
Vijayawada
Email ID: [email protected]
Orcid ID: 0009-0004-8713-3312

Shivam Agarwal4
Assistant Professor, College of Paramedical
Sciences
Teerthanker Mahaveer University Moradabad
U.P, India
Email ID: [email protected]
Orcid ID: 0000-0002-7891-9389

Viswanathan Kaliyaperumal5
Associate Professor, Department of
Prosthodontics,
Saveetha dental college, Saveetha Institute of
Medical and Technical Sciences (SIMATS),
Chennai-600 077, India
E-mail ID: [email protected]
Orcid ID: 0000-0003-2800-9739

Anindita Ghosh6
Intern (bds), Intern,
Oral medicine and radiology, KIIT University
Pincode 751024, Bhubaneswar , India
Email ID: [email protected]

European Journal of Prosthodontics and Restorative Dentistry (2026) 34 (1s), 101–107

Artificial Intelligence-Driven
Prosthetic Rehabilitation in
Partially Edentulous Patients:
Long-Term Clinical
Assessment of ImplantSupported Restorations

In the fields of prosthodontics, implant dentistry, and oral surgery, artificial intelligence (AI) has become a game-changing tool that enhances digital treatment planning, diagnostic accuracy, and restorative rehabilitation results. However, evidence regarding the long-term clinical effectiveness of AI-assisted implant-supported prosthetic rehabilitation remains limited. The present investigation aimed to assess the long-term clinical outcomes, implant survival, prosthetic performance, and patient satisfaction associated with AI-assisted implant-supported prosthetic rehabilitation in partially edentulous patients. A retrospective clinical study was conducted on 80 partially edentulous patients who underwent AI-assisted implant-supported prosthetic rehabilitation. Clinical and radiographic records collected over a follow-up duration of 5–7 years were analyzed. The rehabilitation workflow incorporated AI-based CBCT analysis, digital implant planning, machine learning-assisted prosthetic design, and AI-supported occlusal adjustment. Clinical variables, prosthetic complications, peri-implant tissue conditions, and patient-centered outcomes were evaluated. The implant survival rate observed during the follow-up period was 95.0%. Mean marginal bone loss was 0.86 ± 0.35 mm, while the mean occlusal stability score was 8.64 ± 0.93. Most patients demonstrated no major prosthetic complications and reported high esthetic and functional satisfaction. The mean AI predictive accuracy score was 91.67 ± 4.49%, indicating favorable agreement between AI-assisted planning and clinical outcomes. AI-assisted implant-supported prosthetic rehabilitation demonstrated favorable longterm clinical outcomes, high restorative predictability, and satisfactory patient-centered rehabilitation, supporting the growing role of AI-driven digital workflows in modern prosthodontics. Keywords: Artificial intelligence; Implant dentistry; Prosthodontics; Digital rehabilitation; Implant-supported restorations

Keywords: Alveolar ridge dimensions; Complete dentures; Edentulous residual ridge; Maximum mouth opening; Oral morphometry; Prosthodontics.

Received: 11 03 2026 Revised: 13.04.2026 Accepted: 19.05.2026

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