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Gleb Danilov1, Konstantin Kotik1, Michael Shifrin1

  • 1Laboratory of Biomedical Informatics and Artificial Intelligence, National Medical Research Center for Neurosurgery named after N.N. Burdenko, Moscow, Russian Federation.

概括

重新定义神经外科手术报告的目标变量显著改善了深度学习分类准确性. 这种增强的方法实现了99.5%的准确性,优化了用于医学文本分析的机器学习.

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Data Validation01:03

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Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

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Modeling and Similitude01:12

Modeling and Similitude

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Sensitivity, Specificity, and Predicted Value01:13

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Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

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Goodness-of-Fit Test01:16

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