Mitigating pathogenesis for target discovery and disease subtyping.
Comput Biol Med
; 171: 108122, 2024 Mar.
Article
em En
| MEDLINE
| ID: mdl-38417381
ABSTRACT
Treatments ideally mitigate pathogenesis, or the detrimental effects of the root causes of disease. However, existing definitions of treatment effect fail to account for pathogenic mechanism. We therefore introduce the Treated Root causal Effects (TRE) metric which measures the ability of a treatment to modify root causal effects. We leverage TREs to automatically identify treatment targets and cluster patients who respond similarly to treatment. The proposed algorithm learns a partially linear causal model to extract the root causal effects of each variable and then estimates TREs for target discovery and downstream subtyping. We maintain interpretability even without assuming an invertible structural equation model. Experiments across a range of datasets corroborate the generality of the proposed approach.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Modelos Teóricos
Limite:
Humans
Idioma:
En
Revista:
Comput Biol Med
Ano de publicação:
2024
Tipo de documento:
Article