Visualizing the knowledge structure and evolution of big data research in healthcare informatics

Area of Science:

• Healthcare Informatics
• Bibliometrics
• Data Science

Background:

• The volume of healthcare big data literature is rapidly expanding.
• Few studies offer a deep, visualized analysis of this growing field.
• Understanding the landscape of healthcare big data research is crucial.

Purpose of the Study:

• To conduct a bibliometric analysis of healthcare big data research.
• To identify foundational knowledge and emerging research hotspots.
• To map the innovation pathways and future trends in the field.

Main Methods:

• Bibliometric analysis of relevant literature.
• Trend analysis of paper production and co-authorship.
• Co-occurrence analysis of keywords and author networks.
• Identification of core institutions, countries, and prolific authors.

Main Results:

• Early contributions came from the US, China, UK, and Germany.
• The innovation path spans disease detection/prognosis, health promotion, and nursing.
• Research hotspots include disease (epidemiology, cancer, diabetes), technology (data mining, machine learning), and health services (customized care, elderly nursing).

Conclusions:

• This study provides a comprehensive overview of healthcare big data research.
• It identifies key research areas and future directions for scholars.
• The findings aid in navigating the complex landscape of healthcare informatics.