Application of Artificial Intelligence Techniques for Monkeypox: A Systematic Review
Article
Chadaga, Krishnaraj, Prabhu, Srikanth, Sampathila, Niranjana, Nireshwalya, Sumith, Katta, Swathi S., Tan, Ru-San and Acharya, U. Rajendra. 2023. "Application of Artificial Intelligence Techniques for Monkeypox: A Systematic Review." Diagnostics. 13 (5). https://doi.org/10.3390/diagnostics13050824
Article Title | Application of Artificial Intelligence Techniques for Monkeypox: A Systematic Review |
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ERA Journal ID | 212275 |
Article Category | Article |
Authors | Chadaga, Krishnaraj, Prabhu, Srikanth, Sampathila, Niranjana, Nireshwalya, Sumith, Katta, Swathi S., Tan, Ru-San and Acharya, U. Rajendra |
Journal Title | Diagnostics |
Journal Citation | 13 (5) |
Article Number | 824. |
Number of Pages | 16 |
Year | 2023 |
Publisher | MDPI AG |
Place of Publication | Switzerland |
ISSN | 2075-4418 |
Digital Object Identifier (DOI) | https://doi.org/10.3390/diagnostics13050824 |
Web Address (URL) | https://www.mdpi.com/2075-4418/13/5/824 |
Abstract | Monkeypox or Mpox is an infectious virus predominantly found in Africa. It has spread to many countries since its latest outbreak. Symptoms such as headaches, chills, and fever are observed in humans. Lumps and rashes also appear on the skin (similar to smallpox, measles, and chickenpox). Many artificial intelligence (AI) models have been developed for accurate and early diagnosis. In this work, we systematically reviewed recent studies that used AI for mpox-related research. After a literature search, 34 studies fulfilling prespecified criteria were selected with the following subject categories: diagnostic testing of mpox, epidemiological modeling of mpox infection spread, drug and vaccine discovery, and media risk management. In the beginning, mpox detection using AI and various modalities was described. Other applications of ML and DL in mitigating mpox were categorized later. The various machine and deep learning algorithms used in the studies and their performance were discussed. We believe that a state-of-the-art review will be a valuable resource for researchers and data scientists in developing measures to counter the mpox virus and its spread. |
Keywords | artificial intelligence; monkeypox; mpox; machine learning; deep learning |
ANZSRC Field of Research 2020 | 400306. Computational physiology |
Byline Affiliations | Manipal Academy of Higher Education, India |
National Heart Centre, Singapore | |
Duke-NUS Medical School, Singapore | |
Ngee Ann Polytechnic, Singapore | |
Asia University, Taiwan | |
Singapore University of Social Sciences (SUSS), Singapore |
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https://research.usq.edu.au/item/z1v78/application-of-artificial-intelligence-techniques-for-monkeypox-a-systematic-review
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