建立了基于人工神经网络的肝硬化诊断模型

V. Bostan, B. Pantelimon
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引用次数: 3

摘要

由于患者人数不断增加以及与之相关的严重并发症,肝硬化在国家和全球层面都获得了极大的重视。根据世界卫生组织最近报告的统计数据,世界范围内的肝硬化(肝硬化)是第十大死亡原因:医学科学首先关注的是建立有效的肝硬化诊断算法并实施治疗方案,以实现对并发症的适当管理。基于时间的肝硬化的正确诊断对于防止进一步的肝损害至关重要。这就转化为病人真正的移植机会和预防这种情况下失代偿的风险因素。本文的主要目标是设计一种基于人工神经网络模型的无创方法,仅使用实验室数据即可诊断肝硬化患者。这项前瞻性研究纳入了在加拉蒂“圣安德鲁”急救医院消化科门诊住院或治疗的各种病因肝硬化患者,每3个月监测一次,持续一年。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Creating a model based on artificial neural network for liver cirrhosis diagnose
Liver cirrhosis has acquired a great importance on both national and global levels due to the growing number of ill persons and nevertheless to serious complication associated to it. Worldwide liver cirrhosis (liver cirrhosis) represents the tenth leading cause of death according to recent statistical data reported by the World Health Organization: The prior concern of medical science for is to establish an effective diagnostic algorithm for liver cirrhosis and to implement therapeutic protocols in order to achieve an adequate management of complications. Time based the correct diagnose of liver cirrhosis can be essential in order to prevent further liver damage. That is translated in according the ill patient a real chance for transplantation and preventing decompensation risk factors for this condition. The main goal of this paper is to design a noninvasive method based on an artificial neural network model that will serve to diagnose liver cirrhosis patients by using only laboratory data. The prospective study included patients with various etiologies liver cirrhosis hospitalized or treated in the Gastroenterology Clinic of the Emergency Hospital “St. Andrew” from Galati which have been monitored every 3 months for one year.
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