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Predicting COVID-19 Symptoms From Free Text in Medical Records Using Artificial Intelligence: Feasibility Study.

Josefien Van Olmen1, Jens Van Nooten2, Hilde Philips1

  • 1Department of Family Medicine and Population Health, University of Antwerp, Antwerp, Belgium.

JMIR Medical Informatics
|April 20, 2022
PubMed
Summary
This summary is machine-generated.

An artificial intelligence model, BERTje, can accurately extract COVID-19 symptoms from primary care electronic medical records. This text mining approach transforms unstructured data into valuable insights for large-scale analysis.

Keywords:
COVID-19artificial intelligencecoding procedureelectronic medical recordsfeasibility studynatural language processingprecision modelprediction modelprimary carestructured registrytext mining

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Area of Science:

  • Medical Informatics
  • Natural Language Processing
  • Public Health

Background:

  • Electronic medical records (EMRs) offer large-scale clinical practice analysis opportunities.
  • Free text fields in EMRs contain rich, underutilized clinical information.
  • Structured coding systems like ICPC improve data but miss nuances in free text.

Purpose of the Study:

  • Develop a prediction model for analyzing COVID-19 symptoms from out-of-hours care EMR free text.
  • Convert unstructured clinical notes into structured, analyzable symptom data.
  • Enhance large-scale analysis of primary care data for public health insights.

Main Methods:

  • Feasibility study design to assess data, modeling steps, and model performance.
  • Developed a multiclass, multilabel classifier for 27 COVID-19 symptoms.
  • Compared a classical machine learning approach (Binary Relevance) with a deep learning approach (BERTje).

Main Results:

  • The BERTje model achieved the highest performance with a weighted F1 score of 0.70 and an accuracy of 0.38.
  • The domain-adapted BERTje model showed improved performance on less common symptom codes.
  • Classical and deep learning models demonstrated varying but respectable performance metrics.

Conclusions:

  • The BERTje AI model reliably predicts COVID-19 information from primary care EMR free text.
  • Text mining of free text fields in EMRs is a viable method for data analysis.
  • This study encourages further research into utilizing routine primary care data.