title: Toward Big Data Analytics: Review of Predictive Models in Management of Diabetes and Its Complications.
abstract: Diabetes is one of the top priorities in medical science and health care management, and an abundance of data and information is available on these patients. Whether data stem from statistical models or complex pattern recognition models, they may be fused into predictive models that combine patient information and prognostic outcome results. Such knowledge could be used in clinical decision support, disease surveillance, and public health management to improve patient care. Our aim was to review the literature and give an introduction to predictive models in screening for and the management of prevalent short- and long-term complications in diabetes. Predictive models have been developed for management of diabetes and its complications, and the number of publications on such models has been growing over the past decade. Often multiple logistic or a similar linear regression is used for prediction model development, possibly owing to its transparent functionality. Ultimately, for prediction models to prove useful, they must demonstrate impact, namely, their use must generate better patient outcomes. Although extensive effort has been put in to building these predictive models, there is a remarkable scarcity of impact studies.
authors.affiliation: Department of Health Science and Technology, Aalborg University, Aalborg, Denmark simcich@hst.aau.dk.
authors.forename: Simon Lebech
authors.initials: SL
authors.lastname: Cichosz
authors.affiliation: Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
authors.forename: Mette Dencker
authors.initials: MD
authors.lastname: Johansen
authors.affiliation: Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
authors.forename: Ole
authors.initials: O
authors.lastname: Hejlesen
mesh_terms: D020000:Decision Support Systems, Clinical; D003661:Decision Support Techniques; D048909:Diabetes Complications / Q000175:diagnosis*; D003920:Diabetes Mellitus; D019468:Disease Management; D006801:Humans
keywords: diabetes complications; diabetes management; machine learning; predictive models