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Validation of a Novel Traditional Chinese Medicine Pulse Diagnostic Model Using an Artificial Neural Network

机译:新型中医脉诊的验证 使用人工神经网络的模型

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摘要

In view of lacking a quantifiable traditional Chinese medicine (TCM) pulse diagnostic model, a novel TCM pulse diagnostic model was introduced to quantify the pulse diagnosis. Content validation was performed with a panel of TCM doctors. Criterion validation was tested with essential hypertension. The gold standard was brachial blood pressure measured by a sphygmomanometer. Two hundred and sixty subjects were recruited (139 in the normotensive group and 121 in the hypertensive group). A TCM doctor palpated pulses at left and right cun, guan, and chi points, and quantified pulse qualities according to eight elements (depth, rate, regularity, width, length, smoothness, stiffness, and strength) on a visual analog scale. An artificial neural network was used to develop a pulse diagnostic model differentiating essential hypertension from normotension. Accuracy, specificity, and sensitivity were compared among various diagnostic models. About 80% accuracy was attained among all models. Their specificity and sensitivity varied, ranging from 70% to nearly 90%. It suggested that the novel TCM pulse diagnostic model was valid in terms of its content and diagnostic ability.
机译:鉴于缺乏可量化的中药(TCM)脉搏诊断模型,引入了一种新颖的TCM脉搏诊断模型来量化脉搏诊断。内容验证是由一组中医医生进行的。使用原发性高血压对标准进行验证。金标准是通过血压计测量的肱动脉血压。招募了260名受试者(血压正常组139名,高血压组121名)。中医医师在视觉模拟量表上,根据左右八个穴位(深度,速率,规则性,宽度,长度,光滑度,刚度和强度)在左,右穴,关和气穴触诊脉搏,并量化脉搏质量。人工神经网络用于建立区分原发性高血压和正常血压的脉搏诊断模型。在各种诊断模型之间比较了准确性,特异性和敏感性。在所有型号中,精度均达到80%。它们的特异性和敏感性从70%到近90%不等。这表明新颖的中医脉诊模型在其内容和诊断能力方面是有效的。

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