ReviewJournal of clinical medicine2025
AI-Powered Predictive Models in Implant Dentistry: Planning, Risk Assessment, and Outcomes.
Review in Journal of clinical medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Accuracy of Dynamic Computer-Assisted Surgery for Pterygoid Implant Placement in Fully and Partially Edentulous Maxillae: A Retrospective Comparative Study.Medicina (Kaunas, Lithuania) · 2026Article
- Classification Performance of General-Purpose Multimodal Large Language Models Across Orthodontic Radiographic Tasks: A Comparative Study of ChatGPT, Gemini, and Claude.Medicina (Kaunas, Lithuania) · 2026Article
- Minimally Invasive Implant Rehabilitation in Geriatric Patients: A Comprehensive Narrative Review of Contemporary Strategies to Avoid Extensive Bone Augmentation Procedures.Geriatrics (Basel, Switzerland) · 2026Review
- Article
- Review
- Artificial Intelligence in Implant Dentistry: Clinical Validity, Diagnostic Performance, Surgical Planning, and Medico-Legal Implications-A Narrative Review.Dentistry journal · 2026Review
- Maxillary sinus-related adverse event reports associated with endosseous dental implants in the FDA MAUDE database: a retrospective text-mining analysis.BMC oral health · 2026Article
- Development of a Conceptual Implant Stability Index Framework for Computational Risk Assessment in Implant Dentistry.Bioengineering (Basel, Switzerland) · 2026Article
- Evaluating the Quality of Artificial Intelligence-Generated Information on Cleft Lip and Palate: A Comparative Cross-Sectional Study.Healthcare (Basel, Switzerland) · 2026Article
- Robot-Assisted Dentistry: What the Evidence Supports and Which Outcomes Are Still Missing.Cureus · 2026Review
- Retrievability of Fractured Abutment Screws in Dental Implants Using Three Removal Techniques: An In Vitro Pilot Study.Journal of functional biomaterials · 2026Article
- Radiomics as a Decision Support Tool for Detecting Occult Periapical Lesions on Intraoral Radiographs.Journal of clinical medicine · 2026Article
- Editorial: Digital implant dentistry: new developments to enhance clinical workflows and patient care.Frontiers in oral health · 2026Article
- Visualization of artificial intelligence applications in oral disease diagnosis: A bibliometric analysis.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is rapidly transforming the landscape of dental implantology by enhancing every stage of treatment, from diagnostics and digital planning to intraoperative navigation, outcome prediction, and long-term follow-up. This narrative review explores the current and emerging applications of AI technologies in implant dentistry, with a focus on machine learning, neural networks, and computer vision. It examines how AI is utilized in digital implant planning, surgical navigation, peri-implant disease monitoring, risk assessment, and the prediction of treatment outcomes such as peri-implantitis and implant failure. These innovations contribute to more efficient workflows, more personalized treatment strategies, and improved cost-effectiveness of care. Finally, future perspectives and educational implications of AI integration in clinical implantology are discussed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.