Emergence and Evolution of Big Data Analytics in HIV Research: Bibliometric Analysis of Federally Sponsored Studies 2000-2019

摘要: Abstract Background The rapid growth of inherently complex and heterogeneous data in HIV/AIDS research underscores the importance Big Data analytics. Recently, there have been increasing uptakes techniques basic, clinical, public health fields research. However, no studies systematically elaborated on evolving applications We sought to explore emergence evolution analytics HIV/AIDS-related publications that were funded by US federal agencies. Methods identified related seven agencies (i.e., NIH, ACF, AHRQ, CDC, HRSA, FDA, VA) from 2000 2019 integrating NIH ExPORTER, MEDLINE, MeSH. Building bibliometrics Natural Language Processing methods, we constructed co-occurrence networks using bibliographic metadata (e.g., countries, institutes, MeSH terms, keywords) retrieved publications. then detected clusters among as well temporal dynamics clusters, followed expert evaluation clinical implications. Results harnessed nearly 600 thousand HIV/AIDS, which 19,528 relating included bibliometric analysis. showed (1) number has since 2000, (2) institutes close collaborations with China, Canada, Germany, (3) University California system, MD Anderson Cancer Center, Harvard Medical School are most productive started early, (4) was not active disciplines until 2015, (5) topics such genomics, HIV comorbidities, population-based studies, Electronic Health Records (EHR), social media, precision medicine, methodologies machine learning, Deep Learning, radiomics, mining emerge quickly recent years. Conclusions a cross-disciplinary over past two decades. Our findings demonstrated patterns trends prevailing informed fast areas including secondary analysis EHR, Learning future directions