Counterfactual formulation of patient-specific root causes of disease.

Autor: Strobl EV; Department of Psychiatry & Behavioral Sciences, 1601 23rd Avenue South, Nashville, 37232, TN, United States of America. Electronic address: eric.strobl@vumc.org.
Jazyk: angličtina
Zdroj: Journal of biomedical informatics [J Biomed Inform] 2024 Feb; Vol. 150, pp. 104585. Date of Electronic Publication: 2024 Jan 06.
DOI: 10.1016/j.jbi.2024.104585
Abstrakt: Objective: Root causes of disease intuitively correspond to root vertices of a causal model that increase the likelihood of a diagnosis. This description of a root cause nevertheless lacks the rigorous mathematical formulation needed for the development of computer algorithms designed to automatically detect root causes from data. We seek a definition of patient-specific root causes of disease that models the intuitive procedure routinely utilized by physicians to uncover root causes in the clinic.
Methods: We use structural equation models, interventional counterfactuals and the recently developed mathematical formalization of backtracking counterfactuals to propose a counterfactual formulation of patient-specific root causes of disease matching clinical intuition.
Results: We introduce a definition of patient-specific root causes of disease that climbs to the third rung of Pearl's Ladder of Causation and matches clinical intuition given factual patient data and a working causal model. We then show how to assign a root causal contribution score to each variable using Shapley values from explainable artificial intelligence.
Conclusion: The proposed counterfactual formulation of patient-specific root causes of disease accounts for noisy labels, adapts to disease prevalence and admits fast computation without the need for counterfactual simulation.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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