Actively Recruiting
An Exploratory Study on the Prediction of Recurrence Risk of Bipolar Disorder Using Sentiment Analysis Technology Based on Multi-modal Feature Fusion
Led by Shanghai Mental Health Center · Updated on 2026-05-07
400
Participants Needed
1
Research Sites
87 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
Bipolar disorder (BD) has become a significant public health problem with complex clinical manifestations, difficult treatment, and poor prognosis. However, there is still a lack of effective biological markers for diagnosing and predicting recurrence. Sentiment analysis computing usually refers to using machine equipment to classify, identify, interpret, and imitate human emotions. However, current multi-modal emotion analysis research is mainly based on one or two modalities. Due to the diversity and complexity of patients' emotional expressions, this single- and dual-modal information analysis is far from enough for accurate discrimination of emotional symptoms. Only emotion analysis technology based on multi-modal feature fusion can make more precise and effective judgments. The current project is based on our previous research on cognitive neuroimaging and big data analysis of bipolar disorder. The investigators plan to enroll 200 BD patients who meet DSM-5 diagnostic criteria and 200 healthy controls. The investigators will use sentiment analysis technology with multi-modal feature fusion (text data, audio and visual modalities, eye movements, and electrophysiology) to identify BD recurrence. Biological markers for risk prediction and an algorithm model for joint judgment of multi-source information will be established to analyze the characterization data. The effectiveness of this recurrence prediction model will be further verified and optimized through a large-sample, prospective cohort study design. It is hoped that it can provide a new method for predicting the recurrence risk of BD patients. In the near future, clinical decision-making aids based on this auxiliary method can be developed, and the translational application value of clinical diagnosis and treatment can be explored.
CONDITIONS
Official Title
An Exploratory Study on the Prediction of Recurrence Risk of Bipolar Disorder Using Sentiment Analysis Technology Based on Multi-modal Feature Fusion
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Patients who have previously met or currently meet the diagnostic criteria for bipolar disorder according to DSM-5, whose condition and treatment are currently stable, and who cooperate with the assessment
- Age 18 years and less than 65 years
- Han Chinese ethnicity
- Sufficient visual and auditory abilities to complete the necessary examinations for the study
- Understanding the study content and signing the informed consent form. If unable to sign personally, a relative or guardian may sign on their behalf
- Healthy controls must match patient group gender
- Healthy controls must have no family history of mental illness
You will not qualify if you...
- Presence of intellectual disability or other conditions significantly affecting current mental state
- Serious or unstable physical illness including neurological disorders, heart conditions, hypertension, malignant tumors, immunodeficiency, or blood glucose higher than 12 mmol/L
- Other diseases interfering with test assessment (abnormal indicators more than twice normal value)
- Healthy controls with mental disorders per DSM-5 or suspicious mental symptoms not meeting diagnostic criteria
- Healthy controls with severe physical illness making assessments difficult
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
Shanghai Mental Health Center
Shanghai, China
Actively Recruiting
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
2
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