Article

Causal feature selection using a knowledge graph combining structured knowledge from the biomedical literature and ontologies: a use case studying depression as a risk factor for Alzheimer's disease

2022-07-20

Abstract excerpt

<h4>Background: </h4> Causal feature selection is essential for estimating effects from observational data. Identifying confounders is a crucial step in this process. Traditionally, researchers employ content-matter expertise and literature review to identify confounders. Uncontrolled confounding from unidentified confounders threatens validity, conditioning on intermediate variables (mediators) weakens estimates,...

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Literature Corpus work: dac51555-04b0-5f7f-8930-1301986bb62f
DOI: 10.1101/2022.07.18.500549

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