Application of Large Language Models in Emergency Neurology
Application of Multimodal Large Language Models in Emergency Neurology Diagnosis
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Chuanjie Wu
- Phone Number: +86 18844815888
- Email: gyibingc1@163.com
Study Locations
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Beijing
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Beijing, Beijing, China, 100053
- Xuanwu Hospital, Capital Medical University
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Age ≥18-80 years, male or female.
- Patients seeking emergency neurology care.
- Patients who can provide complete medical records (including consultation recordings, physical examination, test results, etc.).
- Voluntary participation and signing of informed consent.
Exclusion Criteria:
- Patients who directly enter the resuscitation process due to the severity of their condition(e.g., patients who are immediately placed in the ICU).
- Patients with unstable vital signs.
- Patients who are unable to communicate effectively (e.g., severe consciousness impairment or severe cognitive disorders).
- Patients who are currently participating in other clinical trials.
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Patients presenting to the emergency neurology department.
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Using the large language model for diagnosing emergency neurology conditions.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
dignostic accuracy
Time Frame: 1 month
|
To evaluate the consistency between the diagnosis made by large language models for emergency patients and the confirmed diagnosis after inpatient or outpatient visits.
|
1 month
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Feasibility of treatment plans
Time Frame: 1 month
|
Experts use the Emergency Treatment Recommendation Scoring Scale to evaluate the treatment suggestions from conventional methods and large language models.
The maximum score is 5 and the minimum score is 1, with 5 representing strong agreement with the recommendation.
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1 month
|
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dignostic specificity
Time Frame: 1 month
|
A comparison of dianostic specificity between large language model diagnosis and emergency department physicians diagnosis
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1 month
|
|
Diagnostic Sensitivity
Time Frame: 1 month
|
A comparison of dianostic sensitivity between large language model diagnosis and emergency department physicians diagnosis.
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1 month
|
|
False Discovery Rate
Time Frame: 1 month
|
A comparison of the false discovery rate between large language model diagnosis and emergency department physicians diagnosis.
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1 month
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- ALEGN
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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