1. Evolutionary Insights in Ontology: A Bibliometric Analysis of Cognitive Computing Applications in Cancer Research.
- Author
-
Ajibade, Samuel-Soma Mofoluwa, Alhassan, Gloria Nnadwa, Jasser, Muhammed Basheer, ALDharhani, Ghassan Saleh, and Al-Qasem Al-Hadi, Ismail Ahmed
- Subjects
COGNITIVE computing ,CANCER research ,BIBLIOMETRICS ,ONTOLOGY ,GENETIC algorithms - Abstract
The research landscape on cognitive computing algorithms, such as Genetic Algorithms (GA), in Cancer/Tumor and Oncological (CTO) research from 2003 to 2022 was examined using Scopus-indexed publications. Bibliometric analysis was employed to assess social networks and thematic areas of GACTO research. The analysis revealed that researchers published 114 articles and 92 conference papers, representing 55.34% and 44.66% of the total publications (TP=206), respectively. Of these, 129 publications were open access, distributed across Gold, Hybrid Gold, Bronze, and Green mediums. Researchers showed a preference for articles over conference papers. Stakeholder analysis highlighted a robust number of active authors, affiliations, and countries involved in GACTO research. Top performers included Zuherman Rustam (TP=5), Universitas Indonesia (TP=6), and India. Productivity was attributed to the availability of resources such as financial support, with top funders being Universitas Indonesia, the National Natural Science Foundation of China, and Brazil's Conselho Nacional de Desenvolvimento Científico e Tecnológico. Social network analysis indicated a low rate of co-authorship at 18.18%, suggesting limited collaboration at the author level. However, at the national level, collaborative links were stronger, with the largest cluster comprising India, Iran, and the United States, and the smallest including Turkey and the United Kingdom. This reflects better access to resources, funding, and infrastructure at the national level. Hotspot analysis identified three major keywords: genetic algorithms, diseases, and feature extraction. Cluster analysis revealed three focus areas: Precision Health Analytics, Genomic Cancer Profiling, and Integrated AI Diagnosis. In conclusion, the GACTO research landscape actively engages in socially impactful and scientific themes, utilizing computational tools to address challenges posed by cancer and other oncological diseases. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF