Comparison of Different Feature Engineering Methods for Automated ICD Coding

NCT04849195 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 6947

Last updated 2021-04-19

No results posted yet for this study

Summary

Using traditional machine learning classifiers, this study targets on comparing bag-of-words, word2cec and roberta on automated ICD coding related to cardiovascular diseases in Chinese corpus.

Conditions

Interventions

OTHER

No intervention

No intervention

Sponsors & Collaborators

  • China National Center for Cardiovascular Diseases

    lead OTHER_GOV

Principal Investigators

  • Wei Zhao, PhD · China National Center for Cardiovascular Diseases

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-03-01
Primary Completion
2021-04-30
Completion
2021-04-30

Countries

  • China

Study Locations

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Entities

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04849195 on ClinicalTrials.gov