The Physician Training Management System Based On Cloud Platform

Physician training is to cultivate qualified clinical doctors who have good professional ethics, solid knowledge on medical theories and excellent clinical skills, and who are able to independently undertake standardized diagnosis and who can treat diseases for the medical institutions at all levels. For a long time, only part of the large and medium-sized hospitals in our country have provided medical trainings for undergraduates, and the overall quality of the grassroots medical staff can’t be improved. In recent years, the experimental work aiming at training grassroots physicians has been launched in many places. With the increasing of training personnels and the expanding of the training scales, the existing manual management on training system or the physician training management system of some individual hospitals can’t meet the needs of training management. Therefore, it is imperative to develop a scientific doctors training management system which targets at all kinds of hospitals and shares training information.In view of the problems above, this paper designed and developed a doctor training management system based on cloud platform. The main study work of this paper includes the following aspects:(1) Related literature at home and abroad was consulted, the development of cloud computing and physician training management system was analyzed, the problems of current physician training management system were summarized in our country, and the main research direction of this article was determined.(2) Cloud computing theories and system-related development techniques were introduced. The service technology and web technology in cloud computing technology and S2 SH framework were analyzed, designed and developed a training management system based on OpenStack cloud computing platform.(3) Due to the traditional artificial subjective factors were weighted on the physician training evaluation, This paper has established a complete set of physician training evaluation system proposed by improved BP neural network to evaluate physician training, the applicability and superiority of MSC-BP2 evaluation method were analyzed via experimental results. The MSC-BP2 neural network takes a rather long time to train a large amount of data. In order to accelerate the training speed of the network, this paper proposed a MapReduce-based MSC-BP2 algorithm by combing the skill advantages of cloud platform in big data storage and the advantages of real-time processing in large-scale storage. And the experimental results show that the algorithm used on cloud computing platform has better performance than that used on the single machines.(4) A general solution is given through the comprehensive consideration of the functional performance index, module partition of the system of physician training management based on cloud platform, then the system has been implemented successfully through perfect demand analysis and detailed design. Compared with other similar systems, in the data processing, the doctor training management system that this paper studied and developed is objective and accurate in the evaluation of training, while training 360 degree data view is shown to be more clear, in addition, comprehensive query is more convenient.(5) The system is stable during the test with LoadRunner and trial operation, whose various performance indicators meet the anticipated target. By using of this system in the physician training work, manpower and material resources were reduced, cost management was decreased, physician training management efficiency was improved.