Intelligent doctor order recommendation method and system based on deep learning

Abstract

The present disclosure proposes a deep learning-based intelligent doctor's order recommendation method and system. The deep learning-based intelligent doctor's order recommendation method includes the following steps: Step (1): constructing a patient condition information database. Step (2): Set the patient to be ordered as the current patient, collect the condition information of the current patient, and judge whether the current patient has medical order information, and if so, perform step (4); otherwise, perform step (3); step (3 ): Determine the patient in the patient’s condition information database that is most similar to the current patient’s condition information, and recommend the most similar patient’s doctor’s order as the current patient’s initial doctor’s order; Step (4): Input the current patient’s condition information into the trained deep learning model M, the output of the deep learning model M is the recommended doctor's order for the current patient. Using deep learning technology to analyze complex patient condition information data and intelligently recommend appropriate doctor's orders.

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

Images