The Study of Relapse Predicting Model for First Episode Depression: Big Data Analysis Based on Clinical Features and Immunochemistry
The Study of Relapse Predicting Model for First Episode Depression: Big Data Analysis Based on Clinical Features and Immunochemistry
Major depressive depression(MDD) is an severe public mental disorders. The purpose of current study is using big data analysis based on clinical features and immunochemistry to investigate and establish an relapse predict model for patients with first episode MDD.
Major depressive depression(MDD) is an severe public mental disorders. The purpose of current study is using big data analysis based on clinical features and immunochemistry to investigate and establish an relapse predict model for patients with first episode MDD.
This study includes two steps. Step 1: Big data analysis based on the clinical features and immunochemical figures of 30000 patients with first episode MDD will be conducted to construct a relapse predict model.
Step 2: 300 patients with first episode MDD will be recruited in this step. Physicians prefer to give corresponding treatment recommendation based on the predictive factors to verify this relapse model.
Inclusion Criteria:
Exclusion Criteria:
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