通过人工智能转变宫癌病理诊断:进展,表现和临床实施障碍
Yue Zhang1, Jiangbo Yuan2, Lin Chen1
1Shaanxi Provincial People's Hospital, Xi'an, China.
Frontiers in oncology
|February 5, 2026
概括
人工智能 (AI) 在改善宫癌病理诊断方面表现有前途,提高了准确性和速度. 然而,为了广泛采用,必须解决标准化和临床验证的挑战.
科学领域:
- 医疗信息学 医疗信息学
- 在瘤学瘤学.
- 病理学 病理学 病理学
背景情况:
- 宫癌的病理诊断面临着病理学家短缺和主观解释等挑战.
- 不一致的检测率会影响诊断可靠性和患者的治疗结果.
研究的目的:
- 系统地审查AI在宫癌病理诊断中的应用状态和发展.
- 确定人工智能技术在这个领域的关键挑战和前景.
主要方法:
- 从2015年1月到2025年8月的研究的系统文献综述.
- 在PubMed/MEDLINE,Scopus和Web of Science中搜索了"人工智能"",宫癌"和"病理诊断"等术语.
- 包括人工智能在组织病理学,免疫组织化学和分子病理学诊断中的研究;不包括动物研究和无关的基因组分析.
主要成果:
- 在1,847项已识别的研究中,包括了56项研究,突出了AI在图像分析和诊断支持方面的潜力.
- 深度学习模型,特别是卷积神经网络,实现了92-98%的准确性,并大大减少了处理时间.
- 实施挑战包括标准化,有限的临床验证和高的基础设施成本.
结论:
- 人工智能为解决病理学家短缺和改善宫癌诊断标准化提供了巨大的潜力.
- 该技术特别适用于资源有限的环境,有助于实现全球消除目标.
- 广泛的临床实施需要克服标准化和验证障碍.
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