The Role of Artificial Intelligence in the Diagnosis of Neoplastic Diseases: A Systematic and Bibliometric Review

Authors

DOI:

https://doi.org/10.3991/ijoe.v20i04.45429

Keywords:

Artificial Intelligence, Machine Learning, Neoplastic Diseases, Cancerous Diseases, Systematic and Bibliometric Review

Abstract


Artificial intelligence (AI) has significantly transformed the medical field, especially in the diagnosis, treatment, and management of oncological diseases. It has had a profound impact on clinical decision-making and has enhanced the quality of life for various populations. This study aims to comprehensively assess the inherent relationship between AI and medicine and to uncover both its positive and negative implications. To achieve a comprehensive understanding, a thorough systematic review of articles was conducted, examining a total of 80 papers published between 2017 and 2023. These articles were carefully selected from well-known open-access databases, such as Scopus, IOPscience, IEEE Xplore, Google Scholar, ResearchGate, and ProQuest. A key finding from this review is that the majority of research on this topic has been published in scientific journals ranked in the first-quartile (Q1), underscoring the importance and high quality of research in this field. The United States, China, India, the United Kingdom, and Canada are the foremost countries in publishing on this topic. Most of the research is published in first-quartile (Q1) journals, representing 51% of the studies. Only 1% of articles appear in third-quartile (Q3) journals. IEEE Xplore is renowned as the primary database for accessing high-impact studies in this field. Future research should prioritize investigating the long-term impact of AI on patient clinical outcomes. International collaborative research could promote innovation and fairness in the implementation of artificial intelligence (AI) in oncology.

Author Biographies

Hector Espinoza Villavicencio , Universidad Nacional Federico Villareal

He works at Servicio Industriales de la Marina (SIMA), Peru. He is a Systems Engineer and holds a Master's degree in Systems Engineering. His research interests are artificial intelligence, cybersecurity and information security, Web Technologies, Cloud Computing and Mobile Applications 

Javier Gamboa-Cruzado, Universidad Nacional Mayor de San Marcos

He works at the Faculty of Systems Engineering of the Universidad Nacional Mayor de San Marcos, Lima, Perú. He is Doctor in Systems Engineering and Doctor in Administrative Sciences. He has published several papers in international journals and conferences. His research interests are in generative artificial intelligence, machine learning, big data, the internet of things, natural language processing, and business intelligence. (email: jgamboa65@hotmail.com).

Jefferson López-Goycochea, Universidad de San Martín de Porres

He works at the Faculty of Engineering and Arquitecture of the Universidad de San Martín de Porres, Perú. He is Doctor in Education and a PhD candidate in Information Systems Engineering, he is Industrial Engineer and has a Master's degree in Computer and Systems Engineering. His research interests are in cloud computing, knowledge management, and machine learning. 

Luis Soto Soto, Universidad Nacional Mayor de San Marcos

He is Industrial Engineer, Master in Systems Engineering, PhD in Systems Engineering. He is a professor in different undergraduate and graduate programs at the Universidad Nacional Mayor de San Marcos. He is dedicated to deep research and implementations in topics such as machine learning, big data and software development. General Manager of a Project Company. 

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Published

2024-03-04

How to Cite

Espinoza Villavicencio, H., Gamboa-Cruzado, J., López-Goycochea, J., & Soto Soto, L. (2024). The Role of Artificial Intelligence in the Diagnosis of Neoplastic Diseases: A Systematic and Bibliometric Review . International Journal of Online and Biomedical Engineering (iJOE), 20(04), pp. 43–68. https://doi.org/10.3991/ijoe.v20i04.45429

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Papers