人工智能有助于诊断口腔潜在恶性疾病:系统审查和元分析
D Horvath1,2, A Fekete1,3, P Martinekova1
1Centre for Translational Medicine, Semmelweis University, Budapest, Hungary.
JDR clinical and translational research
|January 21, 2026
概括
人工智能 (AI) 工具在从口内照片中识别口腔潜在恶性疾病 (OPMDs) 中显示出高准确性. 它们的高负预测值可以帮助减少对OPMD诊断的不必要的专家转诊.
科学领域:
- 口服药是一种口服药.
- 医学成像医学成像
- 人工智能的人工智能是人工智能.
背景情况:
- 口腔潜在恶性疾病 (OPMDs) 是口腔癌的前体,是一个重大的全球健康问题.
- 早期发现和预防对于改善患者的治疗结果至关重要.
- 人工智能 (AI) 提供了新的非侵入性方法来分析医疗数据,包括临床照片,以协助OPMD诊断.
研究的目的:
- 系统地审查和进行对人工智能的诊断准确性进行元分析,应用于OPMDs的口内照片.
- 将AI诊断性能与组织学检查进行比较,这是当前的黄金标准.
主要方法:
- 在五个主要数据库 (MEDLINE,Embase,Cochrane Library,Scopus,Web of Science) 进行了系统的文献搜索,截至2023年11月10日.
- 包括将AI诊断方法与组织学进行比较的研究.
- 量化分析评估了灵敏度,特异性,正预测值 (PPV),负预测值 (NPV),诊断几率比率 (DOR) 和概率比率 (LR+,LR-) 的95%置信区间 (CI).
主要成果:
- 六项研究分析了来自4,046的898张图像,符合纳入标准.
- 性能最好的AI模型表现出高的诊断准确性.
- 顶级AI架构的整体性能指标包括0.94 (95%CI,0.88-0.95) 的灵敏度和0.95 (95%CI,0.85-0.98) 的特异性.
结论:
- 基于人工智能的诊断工具在从口内图像中识别OPMD病变时具有很高的负预测值.
- 虽然人工智能有可能减少不必要的专家咨询,但临床判断仍然至关重要.
- 需要进一步的前性研究,以将人工智能诊断整合到日常护理中,以加强口腔癌查和早期检测.
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