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Bipolar Disorder and Oxidative Stress Injury Mechanism - Clinical Big Data Analysis Based on Machine Learning

NCT03949218 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 3702

Last updated 2019-05-14

No results posted yet for this study

Summary

This study is a single-center, retrospective, cross-sectional study. We plan to work with our network information center to analysis the related indicators of oxidative stress injury in patients with bipolar disorder based on oxidative stress data. During the study, machine learning was used as a data analysis method to screen out the biomarker risk factors with sensitivity and specificity for early recognition of bipolar disorder from major depression disorder with oxidative stress injury as the core. And then build up effective clinical predictive models for early identification of bipolar disorder, which can predict the early quantitative probabilistic of the onset of bipolar disorder.

Conditions

Sponsors & Collaborators

  • Shanghai Mental Health Center

    lead OTHER

Principal Investigators

  • Yiru Fang · Shanghai Mental Health Center

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2018-11-20
Primary Completion
2018-11-20
Completion
2018-11-20

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 NCT03949218 on ClinicalTrials.gov