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A novel model based on non invasive methods for prediction of liver fibrosis

机译:一种基于非侵入性方法的新型模型,用于预测肝纤维化

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Serial liver biopsies are typically the gold standard for diagnosis of liver fibrosis progression. However, It is associated with serious complications, inconvenient to patients and expensive, the challenge is to substitute the liver biopsy with non-invasive method. The proposed technique is employed to resolve this issue with average accuracy 99.48% for 5-folds cross validation. This accuracy pave the way to utilize classification models as a clinically non-invasive and reliable method to assess the degree of liver fibrosis.
机译:连续肝活组织检查通常是诊断肝纤维化进展的金标准。然而,它与严重的并发症有关,对患者不方便,昂贵,挑战是用非侵入性方法替代肝脏活组织检查。所提出的技术被采用5倍交叉验证的平均精度为99.48 %来解决此问题。这种准确性铺平了利用分类模型作为评估肝纤维化程度的临床非侵入性和可靠方法。

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