Online medical recommendation system and implementation method thereof

Abstract

The invention provides an online medical recommendation system. A patient registers and logs in the system; personal medical information is input; and a home page module, a personal information page module, a medical communication feedback module, a disease community module and a rehabilitation physiotherapy suggestion module are selected for entering. The construction of the recommendation model is based on an improved PSVD method and a knowledge graph method, a prediction score model of a patient to an unscored medical project is constructed by using an established patient-medical project preference matrix, a noise data critical value, a singular value set and the like, then the knowledge graph method is introduced to optimize the result of the PSVD method, a knowledge graph KI is constructed according to a data set, and the prediction score of the patient to the unscored medical project is obtained. The method comprises the steps that KI is established, vector triples in the KI are set, a KI patient interest preference attribute grade model and a medical project positive and negative correlation entity model are established based on the triples, finally, a recommendation model is established by fusing a PSVD method, and a final recommendation result list set SET is obtained.

Description

technical field [0001] The invention relates to an online medical recommendation system and method, in particular to an online medical recommendation system based on an improved knowledge graph and a PSVD method and an implementation method thereof. Background technique [0002] At present, medical personnel in the field of medical and health information still face many problems and challenges in the process of collecting and processing massive data. First, the traditional hospital information storage method can no longer meet the huge demand for medical information storage; second, problems such as insufficient system information, excessive information, information conflict, information dispersion and information errors make it impossible to fully explore the potential value of hospital information data; third, Once the explosive growth of medical data means that the data may face the risk of leakage, it is difficult to guarantee the security and privacy of medical data. T...

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Problems solved by technology

[0003] Aiming at the problem of excessive medical information, the present invention designs a patient-medical item preference matrix, and defines the matrix singular value critical parameter, the critical parameter is set according to the variance model and the matrix singular value set, and removes the marginal data in the matrix; aiming at how to quickly Efficiently recommend items to patients, use the set knowledge graph KI, analyze multiple entities and attributes in KI to establish vector triplets, establish patient interest attribute preferences and positive and negative related entity methods, and give recommendation model solutions; for existing The medical recommendation method has the problems of single recommendation results, sparse data, and data cold start. The design of the present invention is based on the knowledge graph and the improved PSVD method to achieve medical recommendation

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