Predicting Mothers with Postpartum Depression using Machine Learning Approaches
Author:
Affiliation:
1. University of Kelaniya,Department of Statistics and Computer Science Faculty of Sciene,Sri Lanka
2. University of Ruhuna,Department of Interdisciplinary Studies,Sri Lanka
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9904953/9905082/09905186.pdf?arnumber=9905186
Reference25 articles.
1. Machine Learning-Based Predictive Modeling of Postpartum Depression
2. Machine learning-based predictive modeling of postpartum depression Supplementary Materials;shin,0
3. Prediction of Depression among Women Using Random Oversampling and Random Forest
4. Machine Learning Models for the Prediction of Postpartum Depression: Application and Comparison Based on a Cohort Study
5. Machine Learning Models for the Prediction of Postpartum Depression: Application and Comparison Based on a Cohort Study
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1. Prevalence and risk factors analysis of postpartum depression at early stage using hybrid deep learning model;Scientific Reports;2024-02-24
2. Performance Comparison of Machine Learning Techniques for Early Detection of Postpartum Depression Using PRAMS Dataset;2023 IEEE 15th International Conference on Computational Intelligence and Communication Networks (CICN);2023-12-22
3. A Study of Machine Learning Models for Predicting Mental Health Through Text Analysis;2023 1st DMIHER International Conference on Artificial Intelligence in Education and Industry 4.0 (IDICAIEI);2023-11-27
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