Ignite Creation Date:
2025-12-24 @ 11:33 PM
Ignite Modification Date:
2025-12-25 @ 9:22 PM
Study NCT ID:
NCT04682756
Status:
UNKNOWN
Last Update Posted:
2020-12-31
First Post:
2020-12-19
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
A Multicenter Study on Early Diagnosis of NSTE-ACS Patients Based on Machine Learning Model
Sponsor:
First Affiliated Hospital of Xinjiang Medical University
Organization:
Study Overview
Official Title:
A Multicenter Study on Early Diagnosis of NSTE-ACS Patients Based on Machine Learning Model
Status:
UNKNOWN
Status Verified Date:
2020-12
Last Known Status:
ACTIVE_NOT_RECRUITING
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:
Early diagnosis of NSTEMI and UA patients is mainly through the construction of machine learning model.
Detailed Description:
The patients with NSTEMI and UA were included. After manual labeling, the admiss- ion record characteristics of patients were selected. 75% of the data is used to build the model, and 25% of the data is used to verify the validity of the model. Five classification models of one-dimensional convolution (CNN), naive Bayesian (NB), support vector machine (SVM), random forest (RF) and ensemble learning were constructed to identify and diagnose NSTEMI and UA patients. Multi-fold cross-validation and ROC-AUC curve are used to measure the advantages and disadvantages of the models.
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?: