在口腔白血病中基于多维人工智能预测癌症进展
1Division of Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, University of Hong Kong, Hong Kong SAR, China.
Journal of dental research
|October 18, 2025
概括
一个新的AI模型,口腔癌预测,准确地预测口腔潜在恶性疾病患者的口腔癌风险. 该工具整合了患者数据,组织学和生物标志物,以改善癌症进展评估和临床管理.
科学领域:
- 在瘤学瘤学.
- 人工智能的人工智能
- 生物标志物 生物标志物
背景情况:
- 口腔癌通常是由口腔潜在恶性疾病 (OPMD) 引起的.
- 口腔白血病 (OL) 是最常见的OPMD,但癌症风险预测仍然具有挑战性.
- 目前用于OL的风险分层方法存在局限性.
研究的目的:
- 开发和验证基于人工智能 (AI) 的时间到事件模型,OralCancerPredict,用于精确预测OL的癌症进展.
- 整合各种数据类型,包括患者特征,组织学特征和免疫组织化学指标.
主要方法:
- 对456名患者数据和来自OL患者的1312个组织样本进行了回顾性分析.
- 对KRT13和p53免疫组织化学的定量分析与临床和组织病理学数据相结合.
- 使用独立数据集 (119名患者,322个组织样本) 进行模型培训,测试和外部验证.
主要成果:
- OralCancerPredict表现出强的性能,具有较高的一致性指数 (0.855-0.867) 和AUC (0.877-0.882).
- 可解释性分析强调了KRT13/p53表达和世卫组织扩张不良分级的重要性.
- 该模型显示,与现有的分级系统相比,净收益优越.
结论:
- OralCancerPredict准确地预测了OL患者的癌症风险和无进展生存率.
- 可解释的人工智能模型提供了改进的风险分层和临床管理潜力.
- 这种工具可以帮助简化OL患者的干预和密切监测.
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