Application of medical intelligence based on Apriori algorithm in the management of rehabilitation nursing personnel

Abstract With the increasing demand for medical services, the amount of data in the field of health care is gradually increasing in a stepwise manner every year. These medical data actually capture the medical information of patients and the entire diagnosis and treatment process of doctors, and can reflect the actual situation in the medical and health field. Currently, most hospital rehabilitation nurses use simple statistical methods to process medical data, and the use value of medical data resources is limited. To improve the value of using medical information, check the relationship between hidden laws and medical information. As one of the effective methods in the field of data mining, Apriori's basic principle is to use specific association rules to define all common element sets that support exceeding the minimum support threshold, and to create association rules that use a common model to achieve the validity threshold. This article uses Apriori algorithm to detect rehabilitation nursing personnel in hospitals, conduct data mining and exploration on medical data, design and construct a medical intelligence system, and then use Apriori algorithm to conduct research, propose a disease classification model and inpatient flow model, and conduct training and testing through the disease classification model. Finally, 300 hospital rehabilitation nursing personnel have received training in using a medical intelligence system to test the actual performance of the system, which has proven to enable rehabilitation nursing personnel to better understand patient information and provide personalized services.