 This study proposes a new algorithm based on quantum computing to discover causal relationships between variables in small data sets. The algorithm was tested on both artificial and real-world medical data and found to be more accurate than existing methods in the low-data regime. It was also shown to be capable of identifying causal structures in cases where existing methods were unable to do so. Additionally, the potential for implementation on real quantum hardware was discussed. This article was authored by Hideaki Kawaguchi.