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Blockchain Machine learning Based Secure Personal Medical Record Storage and Sharing Platform - DataBlock

机译:基于BlockChain和机器学习的安全个人医疗记录存储和共享平台 - Datablock

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Data is the most important part of machine learning. In the bioinformatics field, the sensitivity of the data is high and due to that, the accessibility of the data for a secondary purpose (e.g.: research) consists of many legal and ethical issues. Due to that in many bioinformatics research collecting the data consume more time than the development phase. There are some researches done to solve the legal and ethical issues by anonymizing the data using encryption, de-identification and perturbation of potentially identifiable attributes. But for some extend those solutions restricted the data breach but on the other hand, anonymized data not performed well during the analysis and mining tasks and some researches done to generate fake data like the real data sets. But those researches not full fill the requirements because of the generated data more restricted to the knowledge of the training data. The evolution of Blockchain provided a secure and trusted way to transfer valuable assets between two unknown parties. This research used Blockchain technology to store and share personal medical data to data scientists. And that will help them to build more accurate and efficient models. It also proposed a machine learning model to predict the authenticity and validity of the personal data based on domain knowledge and the validator's trust percentage.
机译:数据是机器学习中最重要的部分。在生物信息化场中,数据的灵敏度高,并且由于此,次要目的的数据的可访问性(例如:研究)包括许多法律和道德问题。由于许多生物信息学研究,收集数据比开发阶段更多的时间。通过使用加密,去除和扰动可能识别属性的加密,取消识别和扰动来解决数据来解决法律和道德问题的一些研究。但是对于一些扩展这些解决方案限制了数据泄露,而另一方面,在分析和挖掘任务期间,在分析和挖掘任务期间没有进行匿名数据,并完成某些研究以生成真实数据集。但由于生成的数据更受限制为培训数据的知识,这些研究不充分填补这些要求。区块链的演变提供了一种安全可信赖的方式来转移两个未知方之间的有价值资产。本研究使用区块链技术将个人医疗数据存储和分享到数据科学家。这将有助于他们构建更准确和高效的模型。它还提出了一种机器学习模型,以预测基于域知识和验证者的信任百分比的个人数据的真实性和有效性。

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