The role of artificial intelligence in healthcare: a structured literature review
Роль искусственного интеллекта в здравоохранении: структурированный обзор литературы
2021-04-09
SCID: 54.1/smg9j6cr
Discuss with AI
Bibliometrix Rartificial intelligence in healthcareclinical decision-makingpredictive medicinestructured literature review
Figures from the paper
Abstract (AI)
BACKGROUND/INTRODUCTION: Artificial intelligence (AI) in the healthcare sector is receiving attention from researchers and health professionals. Few previous studies have investigated this topic from a multi-disciplinary perspective, including accounting, business and management, decision sciences and health professions. METHODS: The structured literature review with its reliable and replicable research protocol allowed the researchers to extract 288 peer-reviewed papers from Scopus. The authors used qualitative and quantitative variables to analyse authors, journals, keywords, and collaboration networks among researchers. Additionally, the paper benefited from the Bibliometrix R software package. RESULTS: The investigation showed that the literature in this field is emerging. It focuses on health services management, predictive medicine, patient data and diagnostics, and clinical decision-making. The United States, China, and the United Kingdom contributed the highest number of studies. Keyword analysis revealed that AI can support physicians in making a diagnosis, predicting the spread of diseases and customising treatment paths. CONCLUSIONS: The literature reveals several AI applications for health services and a stream of research that has not fully been covered. For instance, AI projects require skills and data quality awareness for data-intensive analysis and knowledge-based management. Insights can help researchers and health professionals understand and address future research on AI in the healthcare field.
Key Findings
1
A structured review identified 288 peer-reviewed Scopus papers on artificial intelligence in healthcare using a reproducible protocol.
2
Effective AI projects require specialized skills and awareness of data quality for data-intensive analysis and knowledge-based healthcare management.
3
Keyword analysis indicates that AI supports diagnosis, disease-spread prediction, and customization of patient treatment pathways.
4
The United States, China, and the United Kingdom produced the highest number of studies in this research area.
5
The emerging literature primarily addresses health services management, predictive medicine, patient data and diagnostics, and clinical decision-making.
Research Object
artificial intelligence in healthcare
Research Subject
the multidisciplinary research landscape, applications, and emerging research gaps concerning AI-enabled health services management, predictive medicine, patient data and diagnostics, and clinical decision-making
Publication Details
Publication Date
2021-04-09
Journal
Publisher
ISSN
Cited by
1096
Open access PDF
Access Type
Author Information
Download PDF
Subscribe to digest
References available in scid.ai4
The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration2009
Artificial intelligence in healthcare: past, present and future2017
The potential for artificial intelligence in healthcare2019
A Systems Approach to Conduct an Effective Literature Review in Support of Information Systems Research2006
Cited by4
Ethical and regulatory challenges of AI technologies in healthcare: A narrative review2024
A Review of the Role of Artificial Intelligence in Healthcare2023
How big data analytics and artificial intelligence facilitate digital supply chain transformation: the role of integration and agility2024
Geographic Information Systems (GISs) Based on WebGIS Architecture: Bibliometric Analysis of the Current Status and Research Trends2024