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Big data approach in healthcare used for intelligent design — Software as a service

机译:用于智能设计的医疗保健中的大数据方法—软件即服务

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Binding technology to healthcare domain for simplifying the process of symptom detection and reliable methods of treatment has attracted vast research. Predictive analysis and recommendation systems have proved noteworthy for symptom detection and have been able to revolutionize healthcare at a very large scale. Our team envisions a web application as the basis of our project inclined towards building a better and efficient platform to simplify the complex procedure of health assessment and monitoring. Using big-data approach, the system that we intend to build shall provide reliable recommendations by comparing user generated data with that of cleansed system data using Apache Spark and IBM Watson services. A self-learning system which auto-upgrades itself with the inflow of data, this web application will provide an user-friendly platform for patients to monitor their symptoms, learn more about the symptoms based on the recommendations given by machine learning algorithm, have received recommendations validated from a doctor and monitor their health on a visual dashboard. Solving the problem of delayed medical attention and inefficient diagnosis, our web application will be one stop solution for everyone's healthcare needs, more broadly - a one-click solution.
机译:将技术绑定到医疗领域以简化症状检测过程和可靠的治疗方法吸引了广泛的研究。事实证明,预测分析和推荐系统对于症状检测非常重要,并且能够大规模革新医疗保健。我们的团队将Web应用程序作为我们项目的基础,旨在构建一个更好,更高效的平台来简化健康评估和监控的复杂过程。使用大数据方法,我们打算构建的系统应通过使用Apache Spark和IBM Watson服务将用户生成的数据与清理后的系统数据进行比较,从而提供可靠的建议。这个网络应用程序是一个自我学习系统,可以随着数据的流入自动进行自我升级,它将为患者提供一个用户友好的平台,以监控患者的症状,并根据机器学习算法给出的建议来了解有关症状的更多信息,由医生验证的建议,并在可视仪表板上监控其健康状况。为了解决医疗延迟和诊断效率低下的问题,我们的Web应用程序将成为满足每个人医疗保健需求的一站式解决方案,更广泛地说,是一键式解决方案。

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