Auxiliary medication decision-making method and intelligent auxiliary medication system

Abstract

The invention discloses an auxiliary medication decision-making method and an intelligent auxiliary medication system. The auxiliary medication decision-making method includes the following steps: Step 1: collecting and acquiring medical data of patients, pre-processing the medical data of patients, and obtaining structure-unified standard clinical data of patients; and Step 2, according to the standard clinical data of patients, obtained in the step 1, predicting applicable drugs for patients through a classification regression tree algorithm, combined with the drug information in a drug database, automatically generating a medication proposal to complete the auxiliary medication decision, wherein the medication proposal is provided for review and use by a physician. The auxiliary medication decision-making method and the intelligent auxiliary medication system can intelligently provide scientific, professional and accurate medication basis, and can assist clinicians and clinical pharmacists to formulate optimal use decisions of drugs, thereby further standardizing drug use.

Description

technical field [0001] The invention belongs to the medical field and the technical field of data processing, and in particular relates to an auxiliary medication decision-making method and an intelligent auxiliary medication system. Background technique [0002] In the process of formulating the current medication plan, first of all, according to the medication suggestions given in the drug instructions, after manually querying the patient's medical data, the physician or pharmacist formulates the initial medication plan based on their own experience and the drug instructions, and adjusts it during the treatment process. optimization. The current method has obvious hysteresis, and the adjustment effect is related to the technical level of the physician or pharmacist, and is easily affected by human factors. [0003] In addition, the incidence of infectious diseases in severe patients is high and the course of disease is fast, and the pharmacokinetic parameters of antibacte...

AI Technical Summary

Problems solved by technology

This method has obvious hysteresis, and the adjustment effect is related to the technical level of physicians or pharmacists. It is seriously affected by human factors, which leads to the failure of anti-infective drugs to achieve the expected effect, which in turn leads to a high failure rate of infection treatment and low patient survival rate in severe patients.

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