Thomas Pamela Bilo, Robertson Daniel H, Chawla Nitesh V
1iCeNSA, Department of Computer Science and Engineering, University of Notre Dame, 384E Nieuwland Science Hall, Notre Dame, 46656 Indiana USA.
2Indiana Biosciences Research Institute, 1345 W. 16th Street Suite 300, Indianapolis, 46202 IN USA.
Appl Netw Sci. 2018;3(1):48. doi: 10.1007/s41109-018-0106-z. Epub 2018 Nov 15.
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.
糖尿病是一个重大的健康问题，超过3000万美国人患有糖尿病。糖尿病的发作会增加各种并发症的风险，包括肾病、心肌梗死、心力衰竭、中风、视网膜病变和肝病。在本文中，我们通过识别进展快和慢的患者，使用基于网络的方法来研究和预测这些并发症的发作。也就是说，给定患者的糖尿病诊断，我们预测发生一种或多种可能并发症的可能性，以及哪些患者会迅速出现并发症。这种“是否会发生并发症”与“并发症发展速度有多快”的结合，可以帮助医生为特定患者制定更好的糖尿病管理方案。
