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Updated: Jan 10, 2026

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一个混合的MCDM和机器学习框架,用于对孕妇的血病风险评估

Shefayatuj Johara Chowdhury1, Tanjim Mahmud2, Farzana Tasnim1

  • 1Department of Computer Science and Engineering, International Islamic University Chittagong, Chittagong 4318, Bangladesh.

Diagnostics (Basel, Switzerland)
|November 27, 2025
PubMed
概括

一个结合多标准决策 (MCDM) 和机器学习的新框架准确地评估了孕妇的血病风险. 这种方法有助于对这一关键的公共卫生问题进行早期检测和明智的孕产妇医疗保健决策.

关键词:
这是一个AHP-TOPSISIS.在 CatBoost 中使用 CatBoost.在 LIME 时代,这就是 SHAP SHAP 的意思.生物医学信息学 生物医学信息学临床决策支持 临床决策支持可以解释的人工智能AI功能选择 功能选择机器学习是机器学习.孕产妇健康 孕产妇健康风险评估 风险评估 风险评估泰拉西米亚的预测

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