Model training method, entity relationship extraction method and device, medium and equipment

A technology of entity relationship and training method, applied in the direction of neural learning method, biological neural network model, character and pattern recognition, etc., can solve the problem of low efficiency of model training, and achieve the effect of reducing the cost of labeling

Inactive Publication Date: 2022-04-08
TIANJIN HAPPY LIFE TECH CO LTD
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Problems solved by technology

[0006] The purpose of the present disclosure is to provide a training and device for extracting a medical entity relationship model, a method and device for extracting a medical entity relati

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  • Model training method, entity relationship extraction method and device, medium and equipment
  • Model training method, entity relationship extraction method and device, medium and equipment
  • Model training method, entity relationship extraction method and device, medium and equipment

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[0033] Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided in order to give a thorough understanding of embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of the specific details being omitted, or other methods, components, devices, steps, etc. may be adopted. In other instances, well-known technical solution...

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Abstract

The invention relates to the technical field of medical data mining, and provides a medical entity relationship extraction model training method and device, a medical entity relationship extraction method and device, a computer storage medium and electronic equipment. The model training method comprises the steps that a training sample set is acquired, and the training sample set comprises a label training sample set and a global label-free training sample set; performing supervised learning training on a preset self-attention model according to the labeled training sample set to obtain an initial self-attention model; and based on the global unlabeled training sample set, updating a reliable training sample set, and when the number of unlabeled sample data in the unlabeled training sample set meets a preset condition, determining a target self-attention model for medical entity relationship model extraction based on the currently updated reliable sample training set. According to the scheme, based on the idea of semi-supervised learning, the training efficiency of the medical entity relationship model and the extraction efficiency of the medical entity relationship can be improved.

Description

technical field [0001] The present disclosure relates to the technical field of medical data mining, in particular, to a training method for a medical entity relationship extraction model, a training device for a medical entity relationship extraction model, a medical entity relationship extraction method, a medical entity relationship extraction device, a computer-readable storage Media, electronic equipment. Background technique [0002] With the advancement of medical informatization, patients' medical records have been converted from handwritten medical records to electronic medical records, resulting in a large amount of electronic medical information. Extracting the entity relationship in electronic medical information can dig out some useful information for medical research. [0003] In related technologies, label data in medical entity relationship extraction is mainly generated by manual labeling, so as to train the medical entity relationship extraction model. ...

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Application Information

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IPC IPC(8): G06F40/295G06F40/289G06F40/117G06K9/62G06N3/04G06N3/08
Inventor 王伟
Owner TIANJIN HAPPY LIFE TECH CO LTD
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