Generalized information with examples on the possibility of using a service-oriented approach and artificial intelligence technologies in the industry of e-Health

Anatolii Petrenko, Oleh Boloban
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Abstract

The object of the research is the review of ways of implementing service-oriented approaches (SOA) and artificial intelligence (AI) technologies in modern healthcare systems. The generalization of these ways will allow to cope with complex modern challenges, such as increasing demand for medical services, growing volumes of data, and the need for high-quality and effective treatment. This work is aimed at this. The field of e-Health is rapidly gaining popularity and combines many different systems. But due to the large number of tools and system providers with different architectures, there is a problem that different systems are difficult or impossible to integrate and connect with each other. It is shown that the use of SOA makes it possible to break down complex systems into separate services that can interact with each other to ensure fast and accurate data processing, effective management of medical resources, and improvement of the quality of medical services. AI can be used to analyze large volumes of medical data, predict risks, diagnose diseases, and develop individualized treatment plans. The use of AI in healthcare systems helps improve diagnostic accuracy, reduce treatment times, and improve patient outcomes. The synergy of SOA and AI in health care systems is important when SOA provides the means to integrate various AI solutions, which allows for the interaction of different services and the exchange of data to ensure effective treatment and collaboration between medical professionals and artificial intelligence systems. Such distribution of systems makes it possible to scale them without affecting other services that are already running. Therefore, it becomes possible to use unified data transfer protocols and combine different services into one system without radically changing the codebase and building additional layers of abstraction for interaction between services that cannot be combined in one system. Examples of the use of SOA and AI in modern health care systems to improve the quality of medical services, optimize resources and ensure an individual and effective approach to patient treatment, which can be used at the next stages of medical reform in Ukraine, are considered.
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关于在电子保健行业中使用面向服务的方法和人工智能技术的可能性的示例的广义信息
本研究的目的是回顾在现代医疗保健系统中实现面向服务的方法(SOA)和人工智能(AI)技术的方法。这些方法的推广将有助于应对复杂的现代挑战,例如对医疗服务的需求不断增加、数据量不断增加以及对高质量和有效治疗的需求。这项工作就是针对这一点。电子卫生领域正在迅速普及,并结合了许多不同的系统。但由于工具和系统提供商数量众多,架构各异,不同的系统之间很难或不可能相互集成和连接。研究表明,SOA的使用使得将复杂的系统分解为可以相互交互的独立服务成为可能,从而确保快速准确的数据处理、有效的医疗资源管理和医疗服务质量的提高。人工智能可以用来分析大量的医疗数据,预测风险,诊断疾病,制定个性化的治疗方案。在医疗保健系统中使用人工智能有助于提高诊断准确性、缩短治疗时间并改善患者的治疗效果。当SOA提供集成各种人工智能解决方案的方法时,SOA和人工智能在医疗保健系统中的协同作用非常重要,这些解决方案允许不同服务的交互和数据交换,以确保医疗专业人员和人工智能系统之间的有效治疗和协作。这样的系统分布使得在不影响其他正在运行的服务的情况下扩展系统成为可能。因此,可以使用统一的数据传输协议并将不同的服务组合到一个系统中,而无需从根本上改变代码库并为无法在一个系统中组合的服务之间的交互构建额外的抽象层。考虑了在现代医疗保健系统中使用SOA和人工智能以提高医疗服务质量、优化资源并确保对患者采取个性化和有效的治疗方法的例子,这些方法可在乌克兰医疗改革的下一阶段使用。
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来源期刊
自引率
0.00%
发文量
89
审稿时长
8 weeks
期刊最新文献
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