Doctor allocation algorithm based on inquiry data

Abstract

The invention discloses a doctor distribution system based on inquiry data, belongs to the field of medical treatment, and is applied to an online inquiry platform. Comprising the steps of obtaining reception data; obtaining distribution identification information corresponding to each doctor; constructing a deep neural network, training to obtain a distribution neural network model, and outputting the distribution neural network model; receiving an inquiry request; acquiring a list of doctors capable of receiving diagnosis; selecting all doctors whose second average processing time is within a preset average processing time range; obtaining an order placing time ratio corresponding to each doctor according to the order placing rate corresponding to each selected doctor and the second average processing time; and distributing the doctor corresponding to the maximum ordering time ratio to the to-be-consulted user. The method has the beneficial effects that by analyzing the treatment time of each doctor on each illness state, the corresponding doctor can be reasonably and quickly allocated to each patient for diagnosis and treatment, and the experience feeling of the patient is improved.

Description

technical field [0001] The invention relates to the medical field, in particular to a doctor allocation algorithm based on consultation data. Background technique [0002] With the popularization of the Internet, the medical industry has also opened online services. The traditional way of consultation is usually to go to the hospital to register or make an appointment for outpatient diagnosis. With the popularization of the Internet, users can also make an appointment online. Duan went to the hospital to receive a doctor's diagnosis, and the doctor and the patient made a diagnosis through face-to-face communication. However, the current diagnosis method still has great limitations, making the patient have to go to the hospital for diagnosis, and because online doctors diagnose and treat patients. Unreasonable distribution leads to difficulty in online appointment or registration, unreasonable use of doctor resources, long queue time for online consultation, and poor user exp...

AI Technical Summary

Problems solved by technology

[0002] With the popularization of the Internet, the medical industry has also opened online services. The traditional way of consultation is usually to go to the hospital to register or make an appointment for outpatient diagnosis. With the popularization of the Internet, users can also make an appointment online. Duan went to the hospital to receive a doctor's diagnosis, and the doctor and the patient made a diagnosis through face-to-face communication. However, the current diagnosis method still has great limitations, making the patient have to go to the hospital for diagnosis, and because online doctors diagnose and treat patients. Unreasonable distribution leads to difficulty in online appointment or registration, unreasonable use of doctor resources, long queue time for online consultation, and poor user experience, which in turn leads to low Gross Merchandise Volume (GMV) of the platform. In view of the above problems, it is urgent to design a doctor allocation algorithm based on consultation data to meet the needs of actual use

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