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Updated: Apr 30, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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一种嵌套交叉验证方法,用于在小型数据集上对机器学习模型的性能评估,用于诊断克鲁茨菲尔特-雅各布病

Rishit Chatterjee, Kazutaka Takahashi

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 5, 2025
    PubMed
    概括

    机器学习助力使用脑脊髓液诊断克鲁茨菲尔特-雅各布病 (CJD). 嵌套交叉验证 (nCV) 提高了对具有有限数据的罕见疾病的模型性能,解决了"小数据问题".

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