Work

Latent Mixture Modeling to Identify Homogeneous Subgroups Predictive of Cerebrovascular Reactivity

Year: 2022

Type: article

Source: The FASEB Journal

DOI: 10.1096/fasebj.2022.36.s1.l8078

Authors: Nicholas A. Rizzi, Theodore DeConne, Ryan Pohlig, Christopher Martens

Institution: University of Delaware

Language: English

Topic: Bayesian Methods and Mixture Models

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W4225405703

FWCI:

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