ArticleFrontiers in oral health2026
A six-level clinical autonomy framework for artificial intelligence in dentistry.
Article in Frontiers in oral health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence in dentistry is rapidly progressing from assistive decision support toward systems capable of executing clinical tasks with increasing autonomy. Despite these advances, the field lacks a structured framework to define, classify, and govern varying levels of clinical autonomy across diagnostic, procedural, and workflow domains in dental practice. This Perspective introduces a dentistry-specific six-level (L0-L5) conceptual clinical autonomy framework characterizing AI systems based on agentic capability, delegated decision authority, human oversight, clinical operating domain, and risk. The proposed taxonomy spans six levels (L0-L5), progressing from human-controlled systems (L0) through assistive (L1), advisory (L2), conditional (L3), and high-autonomy systems (L4), to full operational autonomy within defined clinical contexts (L5). A key inflection point is identified at Level 3, where systems transition from advisory outputs to delegated execution within defined clinical boundaries, marking a shift in responsibility, regulatory classification, and safety requirements. The framework emphasizes functional-level classification, recognizing that autonomy may vary across perception, decision-making, and execution components within hybrid systems. It integrates human-centered considerations, including clinician-AI interaction, transparency, interpretability, and evolving accountability models, while emphasizing inclusive validation and context-aware deployment across diverse patient populations and healthcare settings. By linking autonomy levels to proportional governance and staged translational evaluation, this conceptual framework is intended to support discussion of the safe and responsible integration of AI systems in oral healthcare. The framework has not undergone empirical validation or formal consensus development and should therefore be interpreted as a conceptual taxonomy intended to support future research, regulatory discussion, and refinement.
Indexed as
Identifiers
What Socratic 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 Socratic graph.