Identifying Patterns of Depression Comorbidities Using Association Rule Learning: Insights from Maryland Medicaid Data

This study demonstrates the utility of association rule learning for detecting clinically relevant patterns of depression comorbidities, including variations by age and sex. The identified rules could inform clinical practice by improving targeted screening, facilitating early diagnosis, and guiding management strategies for patients with multiple chronic conditions.