AI-based Multi-center Research on Identification/Classification/Aided Diagnosis of Mood Disorder

Zhejiang University

Status: Enrolling

Conditions: Major Depression; Bipolar Disorder Depression

Study type: Observational

Funder types: Other

Identifiers

NCT05608135

IIT20210021B-R2

Details and patient eligibility

About

At present, diagnosis and recognition of depression and bipolar disorder are mainly based on subjective evidence such as clinical interview and scale evaluation. The corresponding diagnosis basis has some shortcomings, such as poor diagnostic reliability and failure in early identification of bipolar disorder. Therefore, it is of great significance to explore objective diagnostic indicators to remedy the deficiencies.

Therefore，the investigators collect psychological and physiological information data of patients with bipolar disorder and depression.Then the investigators aim to construct and verify the multidimensional emotion recognition model to analyze the personality characteristics, negative emotions and cognitive reactions of different individuals, and form a systematic accurate recognition and evaluation tool.

Enrollment: 960 estimated patients

Sex: All

Ages: 15 to 55 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

1. Age 15-55, regardless of gender;
2. The brief International Neuropsychiatric Interview Chinese version (MINI) was used to meet the diagnostic criteria for DSM-IV-TR depressive disorder or bipolar disorder (type I);
3. Total score of Hamilton Depression Scale (HAMD-17) ≥17, and Young's Manic Scale (YMRS) ≤6;
4. Junior high school or above.

Exclusion criteria

1. The patient conforms to DSM-IV schizophrenia and related spectrum disorders.
2. The patient has a history of severe head trauma (loss of consciousness for more than 5 minutes), current or previous history of epilepsy, intracranial hypertension, or other serious neurological diseases;
3. Had a history of alcohol or psychoactive substance abuse/dependence in the 6 months prior to the test;
4. Those considered unsuitable for inclusion by the researcher.