NCBI PubMed Central
open access
Machine Learning Approaches to Identify Influential Factors of the Comorbid Psychiatric Symptoms and Hypertension Among Rural Adults in Bangladesh: A Cross-Sectional Study.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Mental Health Crisis Among Married Women in Bangladesh: Risk Factors and the Role of Misdiagnosis.#630747
- Application of the Health Belief Model using the PRECEDE-PROCEED framework for community-based hypertension control in rural Bangladesh: a cluster randomized trial protocol#403781
- Interpretable Machine Learning for Predicting Early Mental Health Care-Seeking Among Reproductive-Age Women in Bangladesh Using BDHS 2022 Data#5051
- Identifying Key Determinants of Fertility Among Women in Bangladesh Using Machine Learning Tools: Evidence From the BDHS 2022.#923577
- Machine learning-based prediction and risk factor analysis of depression among reproductive-aged women in Bangladesh: Findings from the BDHS 2022.#358524
Record · ID 430762
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive