Your browser doesn't support javascript.
loading
Predicting onset of complications from diabetes: a graph based approach.
Thomas, Pamela Bilo; Robertson, Daniel H; Chawla, Nitesh V.
Afiliação
  • Thomas PB; 1iCeNSA, Department of Computer Science and Engineering, University of Notre Dame, 384E Nieuwland Science Hall, Notre Dame, 46656 Indiana USA.
  • Robertson DH; 2Indiana Biosciences Research Institute, 1345 W. 16th Street Suite 300, Indianapolis, 46202 IN USA.
  • Chawla NV; 2Indiana Biosciences Research Institute, 1345 W. 16th Street Suite 300, Indianapolis, 46202 IN USA.
Appl Netw Sci ; 3(1): 48, 2018.
Article em En | MEDLINE | ID: mdl-30581983
Diabetes is a significant health concern with more than 30 million Americans living with diabetes. Onset of diabetes increases the risk for various complications, including kidney disease, myocardial infractions, heart failure, stroke, retinopathy, and liver disease. In this paper, we study and predict the onset of these complications using a network-based approach by identifying fast and slow progressors. That is, given a patient's diagnosis of diabetes, we predict the likelihood of developing one or more of the possible complications, and which patients will develop complications quickly. This combination of "if a complication will be developed" with "how fast it will be developed" can aid the physician in developing better diabetes management program for a given patient.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Appl Netw Sci Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Appl Netw Sci Ano de publicação: 2018 Tipo de documento: Article