ReviewDento maxillo facial radiology2023
Personalized dental medicine, artificial intelligence, and their relevance for dentomaxillofacial imaging.
Review in Dento maxillo facial radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.
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
48 citing papers in PubMed, 1 synthesis or guideline pooled it, 81 citations in OpenAlex.
- Current evidence of generative artificial intelligence specifically developed for dental and maxillofacial radiology: a systematic review.Dento maxillo facial radiology · 2026Pooled it
- Structure of AI Responses With Complex Patient Analysis for Patient Alternatives and Patient Modifiers.European journal of dental education : official journal of the Association for Dental Education in Europe · 2026Article
- Commercial large language models for oral cavity cancer staging using descriptive pre-treatment MRI reports: ready for standalone use in clinical practice?Insights into imaging · 2026Article
- Using of artificial intelligence to evaluate image quality for interproximal bone level assessment on bitewing radiographs.Imaging science in dentistry · 2026Article
- A comparison of panoramic views reformatted from CBCT scans using manual or automated workflows: an evaluation of geometric accuracy and subjective image quality.Clinical oral investigations · 2026Article
- Diagnostic Accuracy of Clinical Decision Support Systems ORADIII and ORAD DDx to Histopathological Diagnosis of Jaw Lesions.Mayo Clinic proceedings. Digital health · 2026Article
- Article
- Exploring the Feasibility of P7 Medicine Principles in Dental Practice (P7 Dentistry).Journal of dentistry (Shiraz, Iran) · 2026Article
- Awareness and perceptions of AR/VR in dentistry: a cross-sectional study among Turkish dental students.BMC medical education · 2026Article
- Dental students' knowledge, perceptions, and educational needs regarding artificial intelligence: a multinational cross-sectional survey.BMC medical education · 2026Article
- Revolutionizing endodontics: the impact and innovations of artificial intelligence.BMC oral health · 2026Review
- Artificial intelligence for the detection and diagnosis of oral and maxillofacial lesions: evidence, limitations, and future directions.Brazilian oral research · 2026Review
- Personalized dentistry: Enhancing outcomes through patient-centered innovation.Bioinformation · 2026Article
- Host-microbiome-immune disequilibrium in oral disease: mechanisms, dysbiosis, and precision therapeutics.Frontiers in immunology · 2026Review
- MicroRNAs in periodontal disease: from pathogenic mechanisms and RANKL/OPG regulation to nanoparticle delivery and personalized medicine.Frontiers in immunology · 2026Review
- How artificial intelligence is reshaping citation impact in oral and maxillofacial radiology journals: an 8-year analysis with editorial and clinical implications (JCR 2017-2024).Frontiers in research metrics and analytics · 2026Article
- Knowledge and awareness of artificial intelligence among dental OPD patients at Patna medical college hospital.Bioinformation · 2026Article
- Quantum Computing in Drug Discovery Techniques, Challenges, and Emerging Opportunities.Current drug discovery technologies · 2026Review
- Detection accuracy of an AI platform for dental treatment features on panoramic radiographs - tooth- and patient-level analyses.Scientific reports · 2025Article
- AI-Based Detection of Dental Features on CBCT: Dual-Layer Reliability Analysis.Diagnostics (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Personalized medicine refers to the tailoring of diagnostics and therapeutics to individuals based on one's biological, social, and behavioral characteristics. While personalized dental medicine is still far from being a reality, advanced artificial intelligence (AI) technologies with improved data analytic approaches are expected to integrate diverse data from the individual, setting, and system levels, which may facilitate a deeper understanding of the interaction of these multilevel data and therefore bring us closer to more personalized, predictive, preventive, and participatory dentistry, also known as P4 dentistry. In the field of dentomaxillofacial imaging, a wide range of AI applications, including several commercially available software options, have been proposed to assist dentists in the diagnosis and treatment planning of various dentomaxillofacial diseases, with performance similar or even superior to that of specialists. Notably, the impact of these dental AI applications on treatment decision, clinical and patient-reported outcomes, and cost-effectiveness has so far been assessed sparsely. Such information should be further investigated in future studies to provide patients, providers, and healthcare organizers a clearer picture of the true usefulness of AI in daily dental practice.
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.