The role of artificial intelligence in healthcare: a structured literature review

Роль искусственного интеллекта в здравоохранении: структурированный обзор литературы
Silvana Secinaro, Davide Calandra, Aurelio Secinaro, Vivek Muthurangu, Paolo Biancone
2021-04-09

Bibliometrix Rartificial intelligence in healthcareclinical decision-makingpredictive medicinestructured literature review
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.
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A structured review identified 288 peer-reviewed Scopus papers on artificial intelligence in healthcare using a reproducible protocol.
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Effective AI projects require specialized skills and awareness of data quality for data-intensive analysis and knowledge-based healthcare management.
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Keyword analysis indicates that AI supports diagnosis, disease-spread prediction, and customization of patient treatment pathways.
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The United States, China, and the United Kingdom produced the highest number of studies in this research area.
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The emerging literature primarily addresses health services management, predictive medicine, patient data and diagnostics, and clinical decision-making.

artificial intelligence in healthcare

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

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2021-04-09
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Silvana Secinaro
Davide Calandra
Aurelio Secinaro
Vivek Muthurangu
Paolo Biancone
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