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Early Warning and Classification Model for Acute Non-traumatic Chest Pain

Chest Pain Clinical Trial

Official title:
A Prospective Study of Acute Nontraumatic Chest Pain - Warning and Classification

Clinical Trial Summary

Acute non-traumatic chest pain is one of the common causes of presentation in emergency patients, but the causes of acute non-traumatic chest pain are complex, the severity of the condition varies greatly, and the specificity of symptoms is not high. Machine learning and intelligent auxiliary models can greatly shorten the time of clinical decision-making, and improve the accuracy of etiological diagnosis in patients with chest pain, reduce the rate of misdiagnosis and missed diagnosis, and provide a clear direction for further treatment.

Clinical Trial Description

Prospective observational studies used outpatient and follow-up information to construct an auxiliary early warning model of acute non-traumatic chest pain based on federated learning, and optimized the accuracy of early warning models through retrospective and prospective studies of large cohort data, and established an efficient and stable early warning and classification model for acute non-traumatic chest pain. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT06196307
Study type Observational [Patient Registry]
Source Beijing Anzhen Hospital
Contact Xiaonan He, Professor
Phone 15001108399
Email hxndoctor@126.com
Status Recruiting
Phase
Start date August 30, 2022
Completion date January 30, 2025
View Details
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