Data mining in diabetes

Authors

  • Franklin Ábalos Municipal Diabetes Center, Santiago del Estero, Argentina
  • José Retamosa Regional Hospital, Santiago del Estero, Argentina
  • Mónica Roldán Independence Hospital, Santiago del Estero, Argentina
  • Alejandro Ábalos Regional Hospital, Santiago del Estero, Argentina
  • Patricia Lettari Independence Hospital, Santiago del Estero, Argentina
  • Ruth Rojo Social Work of the Provincial Public Employee, Santiago del Estero, Argentina

DOI:

https://doi.org/10.47196/diab.v49i3.204

Keywords:

data mining, diabetes, technology

Abstract

Data mining is a relatively new tool that allows finding out unknown associations in databases. Its use in medicine is scarce and therefore in diabetes. We describe basic notions with hypothetic examples regarding diabetes, to apply in our daily practice.

Author Biographies

Franklin Ábalos, Municipal Diabetes Center, Santiago del Estero, Argentina

Physician Specialist in Internal Medicine; Director Municipal Diabetes Center, Santiago del Estero

José Retamosa, Regional Hospital, Santiago del Estero, Argentina

Diabetes Specialist Doctor; Physician at the Diabetes Department of the Regional Hospital, Santiago del Estero

Mónica Roldán, Independence Hospital, Santiago del Estero, Argentina

Physician Specialist in Medical Clinic; Physician at the Diabetes Department of Hospital Independencia, Santiago del Estero

Alejandro Ábalos, Regional Hospital, Santiago del Estero, Argentina

Physician Specialist in Nephrology; Physician at the Nephrology Department of the Regional Hospital, Santiago del Estero

Patricia Lettari, Independence Hospital, Santiago del Estero, Argentina

Medical Clinic Specialist; Doctor of the Medical Clinic Department of the Independencia Hospital, Santiago del Estero

Ruth Rojo, Social Work of the Provincial Public Employee, Santiago del Estero, Argentina

Graduate in Nutrition; Nutritionist at the Quality of Life Center (Diabetes); Social Work of the Provincial Public Employee, Santiago del Estero

References

Savage N. Mining data for better medicine. MIT Technology Review. 2011; 38:235-7.

North MA. Data mining for the masses. A global text project book. 2012; 122-24.

Kotu V, Deshpande B. Predictive analytics and data mining: concepts and practice with Rapidminer. Morgan Kaufmann, Elsevier, 2014: 4111.

Chisholm A. Exploring data with Rapidminer. Packt Publishing. 2013: 306-7.

Hofmann M. Data mining use cases and business and analytics applications. Chapman&Hall CRC. 2013; 234-5.

Sumathi S, Sivanandam S. Introduction to Data mining and its applications. Springer. USA. 2006; 732-33.

The DCCT Research Group. Epidemiology of severe hypoglycemia in the diabetes control and complications trial. The American Journal of Medicine. Vol. 90, Issue 4, April 1991, Pages 450-459.

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Published

2023-01-10

How to Cite

Ábalos, F., Retamosa, J., Roldán, M., Ábalos, A., Lettari, P., & Rojo, R. (2023). Data mining in diabetes. Journal of the Argentine Society of Diabetes, 49(3), 77–84. https://doi.org/10.47196/diab.v49i3.204

Issue

Vol. 49 No. 3 (2015): September/December 2015

Section

Original article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Dirección Nacional de Derecho de Autor, Exp. N° 5.333.129. Instituto Nacional de la Propiedad Industrial, Marca «Revista de la Sociedad Argentina de Diabetes - Asociación Civil» N° de concesión 2.605.405 y N° de disposición 1.404/13.

La Revista de la SAD está licenciada bajo Licencia Creative Commons Atribución – No Comercial – Sin Obra Derivada 4.0 Internacional.

Por otra parte, la Revista SAD permite que los autores mantengan los derechos de autor sin restricciones.

 

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