Application of quantum computing to a linear non-Gaussian acyclic model for novel medical knowledge discovery.

ABSTRACT: Recently, the utilization of real-world medical data collected from clinical sites has been attracting attention. Especially as the number of variables in real-world medical data increases, causal discovery becomes more and more effective. On the other hand, it is necessary to develop new causal discovery algorithms suitable for small data sets for situations where sample sizes are insufficient to detect reasonable causal relationships, such as rare diseases and emerging infectious diseases. This study aims to develop a new causal discovery algorithm suitable for a small number of real-world medical data using quantum computing, one of the emerging information technologies attracting attention for its application in machine learning. In this study, a new algorithm that applies the quantum

SUBMITTER: Kawaguchi H 

PROVIDER: S-EPMC10075477 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature