Making periodontal risk visible: the role of artificial intelligence in recall adherence.

IF 2.7 Q3 DENTISTRY, ORAL SURGERY & MEDICINE
Frontiers in dental medicine Pub Date : 2026-09-03 eCollection Date: 2026-01-01 DOI:10.3389/fdmed.2026.1927437
Prajakta Karkare
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引用次数: 0

Abstract

Supportive periodontal care is essential for maintaining periodontal stability after active therapy, yet adherence to periodontal maintenance remains difficult. Once bleeding, halitosis or other presenting concerns improve, some patients may interpret the disease as resolved and the maintenance visit as "just a clean." This Perspective uses the intention-behaviour gap to examine behavioural, financial and health-literacy barriers to continued supportive care. It then considers a narrower, testable hypothesis: artificial intelligence (AI) might assist clinicians in organising clinician-verified periodontal information and presenting it through personalised visual summaries or prompts. Evidence that AI improves periodontal recall attendance is currently sparse; most dental AI research concerns image interpretation or classification, and the only directly relevant periodontal adherence study is proof-of-concept. Proposed risk projections are therefore presented as a distant research concept rather than a clinically validated tool. AI should not replace clinical judgement, and any future system would require validation, transparent uncertainty, consent, governance, equity safeguards and comparison with simpler non-AI interventions.

使牙周风险可见:人工智能在回忆依从性中的作用。
在积极治疗后,支持性牙周护理对于维持牙周稳定性至关重要,然而坚持牙周护理仍然很困难。一旦出血、口臭或其他症状得到改善,一些患者可能会认为疾病已经解决,而维护访问只是“清洁”。本展望利用意向-行为差距来审查行为、财务和健康素养障碍对持续支持性护理的影响。然后,它考虑了一个更狭窄的、可测试的假设:人工智能(AI)可能会帮助临床医生组织经临床验证的牙周信息,并通过个性化的视觉摘要或提示来呈现这些信息。人工智能改善牙周召回率的证据目前很少;大多数牙科人工智能研究涉及图像解释或分类,唯一直接相关的牙周依从性研究是概念验证。因此,提出的风险预测是一个遥远的研究概念,而不是临床验证的工具。人工智能不应该取代临床判断,任何未来的系统都需要验证、透明的不确定性、同意、治理、公平保障,并与更简单的非人工智能干预措施进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.10
自引率
0.00%
发文量
0
审稿时长
13 weeks
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