The Challenge of Big Data and Data Mining in Aging Research

Population growth and the rapid evolution of several technologiesTechnology into almost every human activity have become constant in modern society. Consequently, much informationInformation is generated daily from many sources, such as the worldwide web, mobile phonesMobile phones, wearables, social media, scientific reports, and healthcare informationInformation, resulting in Big DataBig data. Digitization, storage, collection, and particularly the analysis of patterns in these data have led to advances in data sciences (data mining and artificial intelligenceArtificial intelligence) to obtain valuable informationInformation from people’s necessities, demands, hobbies, and activities from such databasesDatabases. On the other hand, agingAging has become one of the main challenges of modern societies since there has been an increase in the prevalencePrevalence of chronic conditions and agingAging-associated outcomesOutcomes. Several advances in biomedicalBiomedical and clinical researchResearch have occurred in recent years with the implementation of omics technologiesTechnology and the digitization of healthcare. In this context, big dataBig data and data mining are powerful tools for obtaining informationInformation that could be used to approach the complexityComplexity of the aging processAging process and its clinical implications. Notwithstanding, big dataBig data and data mining also face challenges such as privacy and security concerns. However, these advancements hold promise for improving public healthPublic health, pharmaceutical development, and our understanding of agingAging.