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The Application of Large Language Model in Emergency Chest Pain Triage

NCT06493175 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 2000

Last updated 2024-07-09

No results posted yet for this study

Summary

This study will evaluate the accuracy and efficiency of large language model in emergency triage.

Conditions

Interventions

DIAGNOSTIC_TEST

Application of large language model in emergency chest pain triage.

The large language model MedGuide-V5 is able to quickly extract key information from a patients description, and by analyzing these descriptions, it provides physicians with a possible initial diagnosis to help them quickly prioritize the treatment of patients.

DIAGNOSTIC_TEST

According to the normal procedures to receive medical treatment

After the artificial intelligence system evaluation, the patients will receive the diagnosis and treatment according to the normal procedure. The overall time of artificial triage, the triage of patients, and other data will be recorded. Patient visits should not be delayed by the use of artificial intelligence systems for evaluation.

Sponsors & Collaborators

  • Jinan Central Hospital

    collaborator OTHER

  • Qingdao Municipal Hospital

    collaborator OTHER

  • Tianjin Medical University General Hospital

    collaborator OTHER

  • The First Hospital of Hebei Medical University

    collaborator OTHER

  • Peking University Third Hospital

    lead OTHER

Principal Investigators

  • Yi-Da Tang, MD, PhD · Peking University Third Hospital

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-12-20
Primary Completion
2024-12-20
Completion
2024-12-20

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

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 NCT06493175 on ClinicalTrials.gov