Research on the construction of prediction model for depressive symptom in the second and third trimester of pregnancy based on artificial neural network - Scorecard - MDSpire
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Research on the construction of prediction model for depressive symptom in the second and third trimester of pregnancy based on artificial neural network
Clinical Scorecard: Development of an Artificial Neural Network-Based Predictive Model for Depressive Symptoms During the Second and Third Trimesters of Pregnancy
At a Glance
Category
Detail
Condition
Depressive Symptoms in Pregnancy
Key Mechanisms
Social support, coping style, personality traits
Target Population
Women in the second and third trimesters of pregnancy
Care Setting
Obstetric outpatient clinics
Key Highlights
42.7% positive rate of depressive symptoms screening
Negative correlation between social support and depressive symptoms
Positive correlation between negative coping and depressive symptoms
Prediction accuracy of 86.9% using artificial neural networks
Logistic regression model accuracy at 79.6%
Guideline-Based Recommendations
Diagnosis
Utilize the second and third trimester depression questionnaire for screening
Management
Formulate nursing measures based on identified influencing factors
Monitoring & Follow-up
Support early identification of depressive symptoms
Risks
Higher rates of depressive symptoms in the second and third trimesters
Patient & Prescribing Data
588 women in the second and third trimesters of pregnancy
Targeted interventions based on predictive model outcomes
