P-ISSN 2587-2400 | E-ISSN 2587-196X
Ejmo Kapak
EJMO Volume : 5 Issue : 3 Year : 2021
EJMO. 2021; 5(3): 239-248 | DOI: 10.14744/ejmo.2021.24856

Artificial Intelligence and Machine Learning in Oncology: Historical Overview of Documents Indexed in the Web of Science Database

Ibrahim Hussein Musa1, Ibrahim Zamit2, Marvellous Okeke3, TosinYinka Akintunde4, Taha Hussein Musa5
1School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, China, 2Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, 3Department of Oncology, Southeast University School of Medicine, Dingjiaoqiao, Gulou District, Nanjing, China, 4Department of Sociology, Hohai University School of Public Administration, Nanjing, China, 5Department of Epidemiology and Health Statistics, Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, China Department of Epidemiology and Health Statistics, Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, China,

Objectives: Artificial Intelligence (AI) and Machine Learning (ML) are innovations contributing to the diagnosis and treatment of cancer. The aim is to present an overview of AI and ML application in oncology research. Methods: Data was retrieved from the web of science. Bibliometrics and R packages and VOSviwer software was used for mapping and network analysis. Results: 214 publications were retrieved written by 1161 authors and published in 133 journals from 1988 to 2021. There has been a steadily increasing trend of research over the past years. AI and ML in oncology research have attracted the interest of the scientific community and the readership. The first ranked documents received a 173 citations score. It covers hot topics related to common mistakes in diagnostic classification in clinical and the potential future opportunities for precision oncology using AI. Aneja S and Thompson RF from the USA are the most productive author. Frontiers in Oncology is the most productive Journal. The United States is leading the research effort on the topics, followed by Korea. The collaboration and network between countries in AL or ML in oncology research were documented. Conclusion: AI and ML in oncology research have attracted the interest of of the scientific community and readership. The trend of research has been steadily increasing globally. Keywords: Artificial Intelligence, bibliometric analysis, machine learning, oncology


Cite This Article

Musa I, Zamit I, Okeke M, Akintunde T, Musa T. Artificial Intelligence and Machine Learning in Oncology: Historical Overview of Documents Indexed in the Web of Science Database. EJMO. 2021; 5(3): 239-248

Corresponding Author: Ibrahim Hussein Musa

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