Big health data: Cardiac remodelling and functional interactions of big brain based implications in body sensor networks

2017 7th International Conference on Communication Systems and Network Technologies (CSNT) Pub Date : 2017-11-01 DOI:10.1109/CSNT.2017.8418563

Debojyoti Seth, Nilanjan Biswas, D. Ghosh

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引用次数: 3

Abstract

Big data analytics enhance modern healthcare by providing personalized medicine based on predictive prescriptions. A model of three layered data sharing for Big Heart Data is developed which uncovers the scope of cardiac remodelling. Remodelling helps in predicting status of heart health informatics based on existing database and prioritizing patient's recent-past cardiac activities. The concept was found to indicate early stages of heart failure leaving ample time to protect the patient from an acute cardiac arrest. A comparative analysis of Activation States and Rest-Task Pair Connectivity of brain is also conducted. Experimental explanations are also provided by recognition process and it opened the scope of not only detecting but also curing dementia by Body Sensor Networking (BSN). BSN can also aid rural cardiac treatments. Big Health Data leads to explore a new era of remotely testing, diagnosing and even curing particular diseases at an early stage without complex medications.

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大健康数据:心脏重塑和身体传感器网络中基于大脑的功能相互作用

大数据分析通过提供基于预测性处方的个性化医疗来增强现代医疗保健。提出了心脏大数据的三层数据共享模型，揭示了心脏重构的范围。重构有助于在现有数据库的基础上预测心脏健康信息的状态，并优先考虑患者最近和过去的心脏活动。这个概念被发现表明心力衰竭的早期阶段，留下足够的时间来保护病人免受急性心脏骤停。并对大脑的激活状态和休息-任务对连通性进行了对比分析。识别过程也提供了实验解释，开启了身体传感器网络(BSN)不仅可以检测痴呆症，还可以治疗痴呆症的领域。BSN还可以帮助农村心脏治疗。大健康数据引领我们探索一个新时代，在不需要复杂药物的情况下，远程测试、诊断甚至治愈早期阶段的特定疾病。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2017 7th International Conference on Communication Systems and Network Technologies (CSNT)

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