Ignite Creation Date:
2025-12-24 @ 3:40 PM
Ignite Modification Date:
2025-12-28 @ 11:51 AM
Study NCT ID:
NCT06779292
Status:
COMPLETED
Last Update Posted:
2025-04-15
First Post:
2025-01-06
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Application of Large Language Models in Emergency Neurology
Sponsor:
Capital Medical University
Organization:
Study Overview
Official Title:
Application of Multimodal Large Language Models in Emergency Neurology Diagnosis
Status:
COMPLETED
Status Verified Date:
2025-04
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Emergency neurology covers a wide range of conditions, often involving urgent situations such as acute cerebrovascular diseases, seizures, central nervous system infections, and consciousness disorders. However, due to the time constraints in emergency care and limited patient information collection, misdiagnosis and missed diagnoses are common issues. Large language models (LLMs) possess powerful natural language processing and knowledge reasoning capabilities, enabling them to directly handle and understand complex, unstructured medical data such as patient medical records, dialogue notes, and laboratory test results. LLMs show broad potential for application in complex medical scenarios. This study aims to evaluate the application value of LLMs in emergency neurology, specifically examining their diagnostic accuracy in emergency neurology conditions, analyzing the feasibility of treatment plans and further examination recommendations proposed by the model, and exploring their potential in improving diagnostic efficiency and aiding decision-making.
Detailed Description:
None
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: