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Construction of an Auxiliary Diagnosis and Efficacy Prediction Model for Adolescent Depression Using Machine Learning Based on Electroencephalogram (EEG) Technology

Construction of an Auxiliary Diagnosis and Efficacy Prediction Model for Adolescent Depression Using Machine Learning Based on Electroencephalogram (EEG) Technology

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400093746
Enrollment
Unknown
Registered
2024-12-11
Start date
2024-12-31
Completion date
Unknown
Last updated
2024-12-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Adolescent Depression

Interventions

Sponsors

Yangzhou Wutaishan Hospital of Jiangsu Province
Lead Sponsor

Eligibility

Sex/Gender
All
Age
13 Years to 17 Years

Inclusion criteria

Inclusion criteria: 1.Adolescent Depression Population: Individuals who meet the DSM-IV diagnostic criteria for adolescent depression and have never undergone systematic treatment or used other psychiatric medications, including antidepressants and mood stabilizers. 2.Normal Group: Individuals who were screened using the Structured Clinical Interview for DSM-IV (SCID) and showed no evidence of psychiatric disorders, with no family history of mental illness. 3. Prior to enrollment, all participants must sign an informed consent form with themselves and their guardians.

Exclusion criteria

Exclusion criteria: 1.History of Chronic Diseases: Conditions such as chronic obstructive pulmonary disease (COPD), asthma, hypertension (>140/95 mmHg), heart disease, liver disease, hematological disorders, diabetes, and tachycardia (resting heart rate > 95 beats per minute). 2.Substance Abuse and Dependence; 3.Neurological Disorders: Including cerebrovascular disease, brain tumors, traumatic brain injury, multiple sclerosis, epilepsy, movement disorders, and migraine under treatment. 4.Individuals Currently Using Respiratory Medications, Cardiovascular Drugs, Anticonvulsants, or Psychoactive Substances.

Design outcomes

Primary

MeasureTime frame
Clinical Parameters;Neurocognitive Measures;Electroencephalographic (EEG) Indicators;

Countries

China

Contacts

Public ContactXiaowei Tang

Yangzhou Wutaishan Hospital of Jiangsu Province

shrimp200@aliyun.com+86 514 87207385

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026