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The evaluation of whether the postoperative rehabilitation results of patients meet the discharge standards is subjective, that is, the doctors determine whether the patients have reached the discharge conditions based on their own experience. To this end, RFID technology is introduced and a method for mining postoperative patient behavior activities is proposed. Because the patient's active path information obtained by RFID during the perioperative period has characteristics such as high redundancy, high dimensions, and high uselessness, before mining, first calculate the condition information entropy of each attribute in the transaction database to reduce the attributes; To improve mining efficiency and reduce useless mining, verify mining is performed on the basis of traditional FP-growth, that is, doctors input association rules that they want to mine, and use the mining results to check whether the patient's postoperative activity behavior meets the standard. The experimental results show that the operation efficiency and mining quality of the algorithm are significantly improved compared with the traditional FP-Growth algorithm, and the operating memory and CPU are also greatly reduced, which has certain clinical feasibility and effectiveness.