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基于Web的阴道和阴道黑色素瘤的预测工具:一个机器学习研究.

Sakhr Alshwayyat1,2,3, Zena Haddadin4, Sara Haddadin5

  • 1King Hussein Cancer Center, Amman, Jordan.

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|September 17, 2025
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阴道恶性黑色素瘤 (VaM) 和阴道恶性黑色素瘤 (VuM) 是一种罕见且具有攻击性的癌症. 机器学习模型预测了存活率,显示阴道黑色素瘤的存活率明显低于阴道黑色素瘤.

关键词:
机器学习 机器学习黑色素瘤是一种黑色素瘤.预后 预后 预后生存分析,生存分析.阴道瘤的发生.阴道瘤的发生.

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科学领域:

  • 在瘤学瘤学.
  • 生殖尿道癌症 生殖尿道癌症
  • 机器学习在医学中的应用

背景情况:

  • 恶性黑色素瘤是一个重大的健康问题,非皮肤形式,如生殖尿路 (GU) 黑色素瘤是特别罕见和攻击性的.
  • 阴道黑色素瘤 (VaM) 和阴道黑色素瘤 (VuM) 是GU黑色素瘤的罕见亚型.
  • 关于VaM和VuM的预后因素和生存结果的数据有限.

研究的目的:

  • 开发基于机器学习 (ML) 的预后模型,用于阴道 (VaM) 和阴道 (VuM) 黑色素瘤.
  • 创建第一个基于Web的预测工具,用于VaM和VuM的生存.
  • 确定影响这些罕见癌症生存的关键预后因素.

主要方法:

  • 利用监测,流行病学和最终结果 (SEER) 数据库 (2000-2020年) 进行队列组装.
  • 用单变量和多变量考克斯回归来进行预后因子查.
  • 开发并验证了五个ML分类器来预测5年生存期,评估AUC-ROC和校准的歧视.

主要成果:

  • 这项研究包括1575名患者:372名VaM,1203名VuM.
  • 针对VuM的5年生存率 (45.4%) 显著高于VaM (15.2%) (P < 0.001).
  • 患者的中位年龄为67岁,中位瘤大小为2.4厘米.

结论:

  • 尿生殖系统黑色素瘤,包括VaM和VuM,表现出积极的临床行为.
  • 手术干预对于管理这些罕见的癌症至关重要.
  • 在VaM和VuM治疗方案中建议谨慎使用化疗和放射治疗.