Abstract
Most decision support systems for diabetes management are unable to adapt to the specific functional requirements of patients and physicians. Each physician has a different clinical experience, so she/he expects a specific decision-making scheme, and each patient has a different health plan that requires personalized care. Also, current support systems may be incapable of adapting to rapid changes in demand, especially as the change and renewal guidelines of clinical systems are often revised. To address such limitations, we introduce DiabSoft, a medical decision support system that prevents, monitors, and treats diabetes. DiabSoft relies on data interchange and integration to generate medical recommendations for patients and health care professionals.
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Acknowledgements
The authors are grateful to the National Technological Institute of Mexico (Tecnológico Nacional de México) for supporting this work. This research paper was also sponsored by Mexico’s National Council of Science and Technology (CONACYT) and the Secretariat of Public Education (SEP) through the PRODEP program.
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Cruz-Ramos, N.A., Alor-Hernández, G., Sánchez-Cervantes, J.L., Paredes-Valverde, M.A., Salas-Zárate, M. (2018). DiabSoft: A System for Diabetes Prevention, Monitoring, and Treatment. In: Valencia-García, R., Paredes-Valverde, M., Salas-Zárate, M., Alor-Hernández, G. (eds) Exploring Intelligent Decision Support Systems. Studies in Computational Intelligence, vol 764. Springer, Cham. https://doi.org/10.1007/978-3-319-74002-7_7
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DOI: https://doi.org/10.1007/978-3-319-74002-7_7
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