Abstract:  Currently, medical institutions lack effective channels to recommend medical resources through Internet. At the same time, due to the complexity and diversity of medical resource application scenarios, the quality of traditional recommendation algorithms for medical field recommendation is not high. Therefore, a doctor recommendation model based on electronic medical records is proposed by matrix multiplication. The recommendation model takes electronic medical records as research object and uses naive Bayesian classifier to obtain intention departments. According to the information of symptoms, diagnosis and conclusions, the doctor-disease matrix and disease-patient matrix of intention departments are constructed, and the recommended results are calculated by matrix multiplication. The experimental results show that the accuracy of the recommended model is 97.3% and the average accuracy is 95.6%.

Key words: medical, recommendation model, electronic medical record, matrix