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Using artificial neural networks to identify patients with concussion and postconcussion syndrome based on antisaccades

机译:利用人工神经网络识别基于防脱离的脑震荡和后调谐综合征患者

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OBJECTIVE Artificial neural networks (ANNs) have shown considerable promise as decision support tools in medicine, including neurosurgery. However, their use in concussion and postconcussion syndrome (PCS) has been limited. The authors explore the value of using an ANN to identify patients with concussion/PCS based on their antisaccade performance.
机译:客观的人工神经网络(ANNS)在医学中的决策支持工具中表现出相当大的承诺,包括神经外科。 然而,它们在脑震荡和后调谐综合征(PC)的使用受到限制。 作者探讨了使用ANN识别基于其反易分析性能的脑震荡/ PC患者的价值。

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