Research Progress in Biomedical Big Data

Abstract

Currently, the value in biomedical big data has been ascending. Notable sources of biomedical big data include medical claims data, electronic medical records, public health data, medical research data, medical market and costs data, individual behavior and mentality data, human genetics and omics data, social demography data, environmental and geographic information data, and health network and media data. Biomedical big data can be applied to conduct omics studies and association studies among different omics, quickly search for biomarkers and develop new drugs, rapidly screen unknown pathogens and find suspicious agents, carry out the real-time implementation of biological monitoring and public health surveillance, prevent and control of emerging infectious diseases, understand the changing spectrum of diseases in the population, evaluate the efficacy and safety of drugs and vaccines in real world, conduct precise health management, and allow more powerful work on data mining. Meanwhile, biomedical big data does face challenges, including standardization and normalization of data collection, merging of current data islands, computer management of massive data, efficient use of data for research and practice, and lack of talents with the comprehensive expertise in both biomedicine and information technology. Biomedical big data will change the pattern of medical practice and improve the quality of healthcare services.