Hospitalization expense prediction method and device based on artificial intelligence, and computer equipment

Abstract

The invention discloses a hospitalization expense prediction method and device based on artificial intelligence, and computer equipment, and relates to the technical field of artificial intelligence and digital medical treatment. The method comprises that: firstly, according to hospitalization medical data of existing regional hospitals, a hospitalization cost prediction model of the existing regional hospitals is obtained through training; and if the hospitalization medical data of the target hospital in the new region does not meet the data conditions which can be used for training to obtain a standard model, transfer learning processing is performed based on the hospitalization cost prediction model of the existing region hospital to obtain the hospitalization cost prediction model of the target hospital in the new region, and then the hospitalization cost required by hospitalization treatment of the target user in the new regional target hospital is predicted. According to the invention, the hospitalization cost prediction accuracy of the hospital can be improved under the condition that the hospital medical data is limited. In addition, the invention also relates to a block chain technology, and hospitalization medical data can be stored in a block chain to ensure data privacy and security.

Description

technical field [0001] This application relates to the field of artificial intelligence and digital medical technology, in particular to an artificial intelligence-based hospitalization expense prediction method, device and computer equipment. Background technique [0002] In recent years, medical expenses have remained high and increased year by year, and the problem of "difficult and expensive medical treatment" has increasingly become a hot spot of concern from all walks of life. The incidence of various diseases has been rising, and the subsequent hospitalization expenses have become a heavy burden for people, which has received great attention, especially when the condition is serious and requires hospitalization, expensive hospitalization expenses may sometimes become a huge resistance to active treatment. If patients can understand in advance the cost of later treatment, the expenses they need to bear, and the expenses that can be reimbursed by medical insurance, on t...

AI Technical Summary

Problems solved by technology

[0004] However, if the hospital’s medical data is extremely limited, it will be impossible to construct a hospitalization expense prediction model, or the prediction result of the hospitalization expense prediction model that is barely constructed is very inaccurate, which will affect the accuracy of the hospital’s hospitalization expense prediction

Images