[Literacy for Appropriate Use of Medical Big Data and Artificial Intelligence]

Recent developments have enabled daily accumulated medical information to be converted into medical big data, and new evidence is expected to be created using databases and various open data sources. Database research using medical big data was actively conducted in the coronavirus disease 2019 (COVID-19) pandemic and created evidence for a new disease. Conversely, the new term "infodemic" has emerged and has become a social problem. Multiple posts on social networking services (SNS) overly stirred up safety concerns about the COVID-19 vaccines based on the analysis results of the Vaccine Adverse Event Reporting System (VAERS). Medical experts on SNS have attempted to correct these misunderstandings. Incidents where research papers about the COVID-19 treatment using medical big data were retracted due to the lack of reliability of the database also occurred. These topics of appropriate interpretation of results using spontaneous reporting databases and ensuring the reliability of databases are not new issues that emerged during the COVID-19 pandemic but issues that were present before. Thus, literacy regarding medical big data has become increasingly important. Research related to artificial intelligence (AI) is also progressing rapidly. Using medical big data is expected to accelerate AI development. However, as medical AI does not resolve all clinical setting problems, we also need to improve our medical AI literacy.