Medical service oriented blockchain data credibility evaluation method

M. Wang, Rong Jiang, Yue Yang, Chenguang Wang, Lin Zhang, Liang Yang, Xuetao Pu
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Abstract

In the study of trusted platforms for medical services, many scholars use the tamper-evident property of blockchain and consensus mechanism to ensure the trusted storage and processing of on-chain data, but they ignore the basic and important issue of trustworthiness of blockchain medical data sources, i.e., medical data to be on-chain. The traditional data trustworthiness evaluation method monitors the historical behavior of data subjects, service quality and other characteristics, and then grades the trustworthiness of the data generated by them. However, this evaluation method has great limitations for medical data subjects (patients) who are highly mobile. Therefore, this paper proposes a trustworthiness evaluation method that combines skewed distribution and entropy weight method, classifies medical data and divides multiple evaluation indicators, integrates the weights of each indicator and performs statistical analysis and trustworthiness probability calculation on the indicators, so as to obtain the trustworthiness of the data to be chained and improve the quality of medical services.
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面向医疗服务的区块链数据可信度评价方法
在医疗服务可信平台的研究中,许多学者利用区块链的防篡改特性和共识机制来保证链上数据的可信存储和处理,但忽略了区块链医疗数据源的可信度这一基本而重要的问题,即医疗数据的链上性。传统的数据可信度评价方法通过监测数据主体的历史行为、服务质量等特征,对其生成的数据的可信度进行分级。然而,这种评价方法对于高流动性的医疗数据主体(患者)有很大的局限性。因此,本文提出了一种将偏态分布和熵权法相结合的可信度评价方法,对医疗数据进行分类,划分多个评价指标,整合各指标的权重,对指标进行统计分析和可信度概率计算,从而获得待链数据的可信度,提高医疗服务质量。
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