使用人工智能检测周周病变:一个叙事审查
1Department of Restorative Dental Sciences, Endodontic Division, College of Dentistry, Taibah University, Madinah 42353, Saudi Arabia.
Diagnostics (Basel, Switzerland)
|January 28, 2026
概括
人工智能 (AI) 在检测牙科放射图上周围病变 (PALs) 方面表现有前途,提高了诊断准确度和缩短了解释时间. 需要进一步的研究来将AI纳入常规临床实践.
科学领域:
- 牙科 牙科是指牙科的专业.
- 放射学 放射学是一门学科.
- 人工智能的人工智能
背景情况:
- 周周病变 (PALs) 很常见,需要精确的放射检测才能成功进行内牙治疗.
- 人工智能 (AI) 的进步有可能提高PALs的诊断准确性.
研究的目的:
- 审查基于人工智能的系统用于检测PALs在口腔内外皮放射 (IOPA),全景放射 (OPG) 和圆束计算断层扫描 (CBCT) 的最新证据.
主要方法:
- 用PubMed/MEDLINE和谷歌学者进行了文献搜索,搜索了2021年1月至2025年7月的研究.
- 在IOPA,OPG和CBCT图像上评估AI用于PAL检测的34项研究得到了定性合成.
主要成果:
- 人工智能系统在各种放射学模式中表现出普遍高的诊断性能.
- 人工智能辅助改善了临床医生的表现,减少了解释时间,性能因病变大小和解剖复杂性而异.
- 研究设计中的异质性需要外部验证和标准化报告.
结论:
- 目前的证据支持人工智能作为检测周周病变的有价值的辅助.
- 需要高质量的随机临床试验来评估AI在日常牙科实践中的实施.
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