Identifying individuals at risk of post-stroke depression: Development and validation of a predictive model.

Journal: Saudi medical journal

PMID: 40335101

Abstract

OBJECTIVES: To identify the factors associated with post-stroke depression (PSD) and develop a machine learning predictive model using a large dataset, considering sociodemographic, lifestyle, and clinical factors.

Authors

Saeed A Alqahtani

From the Department of Physiology, College of Medicine, Taibah University, Al-Madinah Al-Munawwarah, Kingdom of Saudi Arabia.

Keywords

Age Factors Aged Depression Female Humans Logistic Models Machine Learning Male Middle Aged Risk Assessment Risk Factors ROC Curve Sex Factors Stroke

External Resources

View on PubMed Access via DOI PubMed (40335101)

Identifying individuals at risk of post-stroke depression: Development and validation of a predictive model.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals