Automatic filling method for medical health record based on speech recognition

Abstract

The invention discloses an automatic filling method for a medical health record based on speech recognition. The method comprises that a training set file used for speech recognition training is obtained in advance; a speech recognition model of a deep neural network is called, and the model is trained to obtain an improved speech recognition model; a condition random field model is called and trained to obtain an information extraction model; voice data to be recognized is input, recognized by the improved speech recognition model automatically, and converted into text data; and feature of each word is obtained to form text feature data, the text feature data is marked, labels of each word in the text feature data is obtained, the words are logged into corresponding data according to the labels, and a record filled automatically is obtained. Compared with an automatic filling result in the prior art, objective facts and main diagnosis are combined, the reliability is very high, medical staff is effectively freed from tedious work of writing the health records of patients manually, the method is simple, and the accuracy is high.

Description

technical field [0001] The invention relates to the technical field of electronic information, in particular to a method for automatically filling in medical and health records based on speech recognition. Background technique [0002] Speech recognition technology has now entered a mature stage and can accurately recognize people's sentences. However, this advanced technology has not been widely applied in the medical system. At the same time, machine learning methods are flourishing in today's society, but in the medical system, it is also underutilized. [0003] At present, most hospitals at home and abroad use electronic information systems to store patients' health and medical information. This kind of health record is usually recorded manually when a doctor sees a patient or a nurse makes a ward round, and is manually entered into a computer for storage. This method of generating health records is not only time-consuming and laborious, but also prone to errors in re...

AI Technical Summary

Problems solved by technology

[0004] However, there are the following major difficulties in combining the existing speech recognition with machine learning and applying it to the automatic filling of patient health records: (1) Different medical workers speak with different voices, intonations and habits. (2) The key issue in applying machine learning methods to the automatic generation of patient medical records is how to ensure the accuracy of generated files, and the main reason for the decrease in accuracy is the selection of Which features to use for model training

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