This paper investigates the automated medical learning and proposes hybrid intelligent framework, called Hybrid Automated Medical Learning (HAML). The goal is the efficient combination of several intelligent components in order to automatically learn the medical data. Multi agents system is proposed by using distributed deep learning, and knowledge graph for learning medical data. The distributed deep learning is used for efficient learning of the different agents in the system, where the knowledge graph is used for dealing with heterogeneous medical data. To demonstrate the usefulness and accuracy of the HAML framework, intensive simulations on medical data were conducted. A wide range of experiments were conducted to verify the efficiency of the proposed system. Three case studies are discussed in this research, the first case study is related to process mining, and more precisely on the ability of HAML to detect relevant patterns from event medical data. The second case study is related to smart building, and the ability of HAML to recognize the different activities of the patients. The third one is related to medical image retrieval, and the ability of HAML to find the most relevant medical images according to the image query. The results show that the developed HAML achieves good performance compared to the most up-to-date medical learning models regarding both the computational and cost the quality of returned solutions.

中文翻译：

---

用于自动化医学学习的混合智能框架

本文研究了自动化医学学习，并提出了混合智能框架，称为混合自动化医学学习（HAML）。目标是多个智能组件的有效组合，以便自动学习医疗数据。多智能体系统是通过使用分布式深度学习和知识图谱来学习医学数据提出的。分布式深度学习用于系统中不同代理的高效学习，其中知识图用于处理异构医疗数据。为了证明 HAML 框架的有用性和准确性，对医疗数据进行了密集模拟。进行了广泛的实验以验证所提出系统的效率。本研究讨论了三个案例研究，第一个案例研究与过程挖掘有关，更准确地说是关于 HAML 从事件医学数据中检测相关模式的能力。第二个案例研究与智能建筑有关，以及 HAML 识别患者不同活动的能力。第三个与医学图像检索有关，HAML根据图像查询找到最相关的医学图像的能力。结果表明，与最新的医学学习模型相比，开发的 HAML 在返回解决方案的计算和成本质量方面取得了良好的性能。以及 HAML 识别患者不同活动的能力。第三个与医学图像检索有关，HAML根据图像查询找到最相关的医学图像的能力。结果表明，与最新的医学学习模型相比，开发的 HAML 在返回解决方案的计算和成本质量方面取得了良好的性能。以及 HAML 识别患者不同活动的能力。第三个与医学图像检索有关，HAML根据图像查询找到最相关的医学图像的能力。结果表明，与最新的医学学习模型相比，开发的 HAML 在返回解决方案的计算和成本质量方面取得了良好的性能。