Artificial Intelligence in Intensive Care Medicine: Bibliometric Analysis

Area of Science:

• Critical Care Medicine
• Artificial Intelligence
• Bibliometrics

Background:

• Growing interest in artificial intelligence (AI) applications within critical care.
• Lack of comprehensive bibliometric studies analyzing global AI research in intensive care.

Purpose of the Study:

• To assess global research trends in AI for intensive care medicine.
• Analyze publication outputs, citations, international coauthorships, and keyword co-occurrences.

Main Methods:

• Bibliometric analysis of 3619 documents from Scopus database until March 2022.
• Included 1198 articles after eligibility screening, analyzed using VOSviewer.
• Computed publication growth, preferred journals, leading countries, collaborations, and institutions.

Main Results:

• Steep publication increase (72.53%) between 2018-2022.
• United States and China dominate publications (55.17%).
• Key research areas include clinical deterioration detection, monitoring, prediction, and classification using neural networks, machine learning, and deep learning.

Conclusions:

• Highlights key AI research areas for improving intensive care unit (ICU) healthcare.
• Provides insights into research trends, collaborations, and future prospects for AI in critical care.
• Emphasizes the need for collaborative efforts to enhance AI model maturity for routine clinical practice.