What is it about?
Monkeypox is a rather rare viral infectious disease that initially did not receive much attention but has recently become a subject of concern from the point of view of public health. Artificial intelligence (AI) techniques are considered beneficial when it comes to diagnosis and identification of Monkeypox through the medical big data, including medical imaging and other details from patients’ information systems. Therefore, this work performs a bibliometric analysis to incorporate the fields of AI and bibliometrics to discuss trends and future research opportunities in Monkeypox. A search over various databases was performed and the title and abstracts of the articles were reviewed, resulting in a total of 251 articles. After eliminating duplicates and irrelevant papers, 108 articles were found to be suitable for the study. In reviewing these studies, attention was given on who contributed on the topics or fields, what new topics appeared over time, and what papers were most notable. The main added value of this work is to outline to the reader the process of how to conduct a correct comprehensive bibliometric analysis by examining a real case study related to Monkeypox disease. As a result, the study shows that AI has a great potential to improve diagnostics, treatment, and public health recommendations connected with Monkeypox. Possibly, the application of AI to Monkeypox study can enhance the public health responses and outcomes since it can hasten the identification of effective interventions.
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Why is it important?
This research is important because it addresses the growing need for effective public health responses to emerging infectious diseases like Monkeypox. With the rise of AI in healthcare, applying these advanced techniques to diagnose and manage Monkeypox could significantly improve the speed and accuracy of medical interventions. AI's ability to analyze vast amounts of medical data, including imaging and patient information, can lead to early detection, personalized treatment plans, and more effective public health recommendations. Moreover, by providing a comprehensive bibliometric analysis, this study identifies key research trends, contributors, and gaps in the literature, helping to guide future research and application of AI in managing Monkeypox and similar diseases. This could enhance global preparedness and response to infectious disease outbreaks.
Perspectives
The perspectives highlighted in this study emphasize the transformative role of AI in the future management of Monkeypox and other infectious diseases. AI's potential to improve diagnostics, treatment plans, and public health strategies is immense, particularly in analyzing large datasets like medical imaging and patient records. The bibliometric analysis reveals key research trends, identifying areas where AI has already made an impact and where future opportunities lie, such as enhancing early detection and intervention strategies. Additionally, this work underscores the need for interdisciplinary collaboration, as AI advancements can drive innovation in public health, ultimately improving responses to disease outbreaks and strengthening healthcare systems.
Yahya Layth Khaleel
Tikrit University
Read the Original
This page is a summary of: Emerging Trends in Applying Artificial Intelligence to Monkeypox Disease: A Bibliometric Analysis, Applied Data Science and Analysis, September 2024, Mesopotamian Academic Press,
DOI: 10.58496/adsa/2024/012.
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