Intelligent medical order recommendation method and system based on deep learning

Abstract

The invention provides an intelligent medical order recommendation method and system based on deep learning. The intelligent medical order recommendation method based on deep learning comprises the following steps that step (1), a patient condition information base is constructed; step (2), a patient waiting for a medical order is set to be a current patient, and condition information of the current patient is collected to judge whether or not the current patient has medical order information, if yes, step (4) is executed, and if not, step (3) is executed; step (3), the patient, closet to thecondition information of the current patient , in the patient condition information base is determined, and the medical order of the closet patient is recommended as an initial medical order of the current patient; step (4), the condition information of the current patient is input into a trained deep learning model M, and the deep learning model M outputs a recommended medical order of the current patient. A deep learning technology is adopted to analyze the complicated condition information data of the patient and intelligently recommend an appropriate medical order.

Description

technical field [0001] The present disclosure relates to the technical field related to medical informatization, and specifically relates to a method and system for recommending intelligent medical orders based on deep learning. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art. [0003] A doctor's order is a doctor's instructions to a patient in terms of diet, medication, and laboratory tests according to the needs of the disease and treatment. According to the patient's condition, it is the main work of the doctor to select the appropriate medical operation and issue a doctor's order, which takes up a lot of working time of the doctor. For doctors, on the one hand, they face a large number of patients and complex situations every day, and the work of issuing doctor's orders takes up a lot of their time; on the other hand, due to inertia of thinki...

AI Technical Summary

Problems solved by technology

[0005] 1. Due to the different conditions of different patients, doctors cannot include all disease classifications into the clinical pathway, which results in doctors being unable to quickly issue medical orders through the clinical pathway system due to the fact that patients are not covered by the clinical pathway system. Therefore, clinical In many cases, the pathway system cannot help doctors improve the efficiency of issuing medical orders

[0006] 2. Doctors need to judge the patient's condition and choose the treatment plan and doctor's order by themselves. The clinical pathway system cannot intelligently judge the patient's condition and recommend doctor's order

[0007] 3. In the clinical pathway system, doctors can only treat according to the pre-set treatment plan, and do not use the advantages of medical big data to analyze the patient's condition to provide doctors with different ideas and help doctors choose more advanced treatment plans

[0008] Therefore, the current doctor's order recommendation system does not play the role of assisting doctors in determining doctor's orders

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