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Method and system for phenotype extraction and phenotype name standardization from electronic medical records

An electronic medical record and phenotype technology, applied in the field of medical text data processing, can solve problems such as high economic costs, and achieve the effects of improving efficiency, improving accuracy, and improving recall accuracy

Active Publication Date: 2021-02-26
TSINGHUA UNIV
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Problems solved by technology

Considering the huge amount of data, if relying on manual structuring, the economic cost will undoubtedly be very high

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  • Method and system for phenotype extraction and phenotype name standardization from electronic medical records
  • Method and system for phenotype extraction and phenotype name standardization from electronic medical records
  • Method and system for phenotype extraction and phenotype name standardization from electronic medical records

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Embodiment Construction

[0040] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention:

[0041] like Figure 8 As shown, the electronic medical record phenotype extraction and phenotype name standardization system of the present invention includes: a phenotype extraction module, an encoding module, a calculation module, and a mapping module, wherein the encoding module includes: an encoder training sub-module and a phenotype encoding sub-module module. The encoding module, calculation module, and mapping module jointly complete the normalization of phenotype names.

[0042] Based on deep learning, the present invention conducts phenotype extraction and phenotype name standardization method for electronic medical record phenotypes, including: phenotype extraction, taking natural sentences of medical record text as original data, using Bi-LSTM model ...

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Abstract

The invention discloses a method for extracting phenotypes from electronic medical records and standardizing phenotype names. The method includes: phenotype extraction, using the natural sentence of the medical record text as the original data, using the Bi‑LSTM model and the CRF model for named entity recognition, and extracting the phenotype entity class; and phenotype normalization, using the LSTM encoder to The cosine similarity between the coding of the non-standard phenotype and the coding of the standard phenotype in the medical records is calculated, and the non-standard phenotype is mapped to the phenotype with the highest cosine similarity. The invention also discloses an electronic medical record phenotype extraction and phenotype name standardization system. The invention improves the accuracy rate of named entity recognition, recall accuracy rate, and accuracy rate of phenotype mapping in electronic medical records; eliminates manual consumption in the process of structuring medical records, improves the efficiency of structuring medical records; can be more efficient and Accurately serve medical data mining, clinical decision support, clinical risk assessment, etc.

Description

technical field [0001] The present invention relates to the technical field of medical text data processing, in particular to a method and system for extracting phenotypes from electronic medical records and standardizing phenotype names based on deep learning. Background technique [0002] In conventional medical electronic records, the main carrier of information is natural language, such as image reports, medication records, disease course reports, and medical record inspection reports. It can be said that these natural language texts contain the main clinical information in the process of patient diagnosis and treatment. On the one hand, in recent years, hospitals at all levels in my country have gradually adopted electronic medical record management systems to replace traditional handwritten medical records, thus accumulating more and more medical electronic records. On the other hand, with the deep integration of information technology represented by big data and arti...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/25G16H10/60
CPCG16H10/60
Inventor 江瑞黄浩
Owner TSINGHUA UNIV
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