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National Cancer Institute scientific production scientometric analysis
Alí Ruiz-Coronel1, José Luis Jiménez Andrade2, Humberto Carrillo-Calvet3
1Instituto Nacional de Cancerología; Centro de Investigación e Innovación en Tecnologías de la Información y Comunicación; Ciudad de México, México.
Scientometrics reveals the National Cancer Institute (INCan) ranks fourth in productivity and sixth in normalized impact among Mexican health institutions. A multidimensional analysis using artificial neural networks provides a more reliable institutional scientometric profile.
Area of Science:
- Scientometrics
- Bibliometrics
- Health Services Research
Background:
- Scientometrics utilizes bibliometric and computational methods to assess scientific publication productivity and impact.
- Understanding institutional scientific output is crucial for research evaluation and strategic development.
Purpose of the Study:
- To develop a multidimensional methodology for profiling the National Cancer Institute (INCan), Mexico.
- To benchmark INCan's scientometric profile against other national health institutions.
Main Methods:
- Analysis of INCan's scientific production from 2007-2017, indexed in Web of Science.
- Application of the ViBlioSOM methodology and LabSOM software, employing artificial neural networks.
- Comparative analysis of INCan's scientometric profile with peer institutions.
Main Results:
- INCan ranked fourth in productivity and sixth in normalized impact among 10 Mexican public health institutions.
- While 51.62% of articles received no citations, a small fraction (0.83%) of highly impactful articles generated 24% of total citations.
- INCan's normalized impact rate exceeded the world average, indicating high productivity.
Conclusions:
- Multidimensional analysis using neural networks offers a more reliable and comprehensive institutional scientometric profile.
- This approach surpasses evaluations based on isolated variables for assessing research performance.
