Leveraging Artificial Intelligence for Biosensors: A Systematic Literature Review with Bibliometrics Approach

Abstract

Artificial Intelligence (AI) driven technologies are percolating into biosensors also nowadays. This study attempted to conduct a systematic review of literature along with bibliometric analysis for thoroughly examining the global trends of research publications in AI and biosensors. Leading research databases were explored for extracting relevant research articles. The review of relevant literature was systematically narrated in year-wise sequence. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement was also formulated to include the relevant research studies for further analysis. Bibliometric analysis was performed to visualize and quantify the research dynamics. Annual scientific production, word cloud, country-based collaboration network, and thematic evolution were constructed. The study provided crucial insights regarding the growth in number of relevant research studies from 2018 onwards. It was found that there was a significant evolution of research themes before, during, and after the COVID-19 pandemic. Researchers from various countries were collaborating among each other to explore this essential research area. This study can have huge implications for the research fraternity and technological experts for exploring AI driven technologies for building innovative biosensors.