title: glUCModel: a monitoring and modeling system for chronic diseases applied to diabetes.
abstract: Chronic patients must carry out a rigorous control of diverse factors in their lives. Diet, sport activity, medical analysis or blood glucose levels are some of them. This is a hard task, because some of these controls are performed very often, for instance some diabetics measure their glucose levels several times every day, or patients with chronic renal disease, a progressive loss in renal function, should strictly control their blood pressure and diet. In order to facilitate this task to both the patient and the physician, we have developed a web application for chronic diseases control which we have particularized to diabetes. This system, called glUCModel, improves the communication and interaction between patients and doctors, and eventually the quality of life of the former. Through a web application, patients can upload their personal and medical data, which are stored in a centralized database. In this way, doctors can consult this information and have a better control over patient records. glUCModel also presents three novelties in the disease management: a recommender system, an e-learning course and a module for automatic generation of glucose levels model. The recommender system uses Case Based Reasoning. It provides automatic recommendations to the patient, based on the recorded data and physician preferences, to improve their habits and knowledge about the disease. The e-learning course provides patients a space to consult information about the illness, and also to assess their own knowledge about the disease. Blood glucose levels are modeled by means of evolutionary computation, allowing to predict glucose levels using particular features of each patient. glUCModel was developed as a system where a web layer allows the access of the users from any device connected to the Internet, like desktop computers, tablets or mobile phones.
authors.affiliation: Department of Computer Architecture and Automation, Universidad Complutense de Madrid, 28040 Madrid, Spain.
authors.forename: J Ignacio
authors.initials: JI
authors.lastname: Hidalgo
authors.affiliation: Endocrinology and Nutrition Service, Hospital Virgen de la Salud, Toledo, Spain.
authors.forename: Esther
authors.initials: E
authors.lastname: Maqueda
authors.affiliation: Department of Computer Architecture and Automation, Universidad Complutense de Madrid, 28040 Madrid, Spain. Electronic address: jlrisco@dacya.ucm.es.
authors.forename: José L
authors.initials: JL
authors.lastname: Risco-Martín
authors.affiliation: C.E.S. Felipe II, Universidad Complutense de Madrid, 28300 Aranjuez, Spain.
authors.forename: Alfredo
authors.initials: A
authors.lastname: Cuesta-Infante
authors.affiliation: C.E.S. Felipe II, Universidad Complutense de Madrid, 28300 Aranjuez, Spain.
authors.forename: J Manuel
authors.initials: JM
authors.lastname: Colmenar
authors.affiliation: Department of Computer Architecture and Automation, Universidad Complutense de Madrid, 28040 Madrid, Spain.
authors.forename: Javier
authors.initials: J
authors.lastname: Nobel
mesh_terms: D000465:Algorithms; D001786:Blood Glucose / Q000032:analysis*; D002908:Chronic Disease; D003198:Computer Simulation; D016208:Databases, Factual; D003920:Diabetes Mellitus / Q000097:blood* / Q000628:therapy*; D006801:Humans; D008490:Medical Informatics; D008962:Models, Theoretical; D008991:Monitoring, Physiologic / Q000379:methods; D015203:Reproducibility of Results; D012648:Self Care; D012984:Software
chemical_list: D001786:Blood Glucose
keywords: Diabetes; Internet; Self-management; Telemedicine; Web applications