在Hyperledger财团网络上的心脏病严重程度识别系统
1Computer Science and Engineering, K.Ramakrishnan College of Engineering, Tiruchirappalli, Tamilnadu, India.
PeerJ. Computer science
|October 23, 2023
概括
本研究介绍了一个基于区块链的系统,使用Hyperledger和基于属性的访问控制 (ABAC) 来增强电子健康记录 (EHR) 的安全性和隐私. 它还集成了高斯的天真贝叶斯算法用于心血管疾病预测,改善了患者护理和数据管理.
科学领域:
- 医疗信息学 医疗信息学
- 区块链技术 区块链技术
- 数据安全 数据安全
背景情况:
- 电子健康记录 (EHR) 对患者护理至关重要,但面临着重大的隐私和安全挑战.
- 现有的电子健康记录系统难以为敏感的患者数据提供强大的保护,防止未经授权的访问和改.
- 区块链技术提供了去中心化和不变的分类账,为安全的健康信息管理提供了有前途的解决方案.
研究的目的:
- 开发一个安全和保护隐私的系统,使用区块链技术共享电子健康记录 (EHR).
- 实施基于属性的访问控制 (ABAC) 机制,以精确控制EHR访问.
- 在区块链框架内整合心血管疾病风险评估的预测模型.
主要方法:
- 一个Hyperledger联盟网络被开发用于安全的EHR共享.
- 基于属性的访问控制 (ABAC) 已经实现了细粒度的数据访问权限.
- 整合了高斯天真贝叶斯算法用于心血管疾病预测.
- 该系统使用Kaggle.com的多个医疗数据集 (心脏病,糖尿病,中风,身体脂肪) 进行了测试.
- 使用Hyperledger Caliper评估性能,测量像延迟和交易率这样的指标.
主要成果:
- 开发的超级账本网络成功增强了EHR共享的隐私和安全性.
- 根据用户属性,ABAC提供了精确的控制对敏感健康记录的访问权限.
- 综合的高斯天真贝叶斯算法在预测心血管疾病风险方面表现出有效性.
- 绩效基准显示了高效的交易率和资源利用率.
结论:
- 拟议的基于区块链的系统有效地解决了EHR管理中的隐私和安全问题.
- 基于属性的访问控制显著提高了医疗信息系统的安全性.
- 预测分析的整合增强了临床决策和患者风险分层.
- 这种方法为安全,高效和智能医疗记录管理提供了一个强大的框架.
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