Risk of Readmission for Diabetes Patients: A Machine Learning Approach

Abstract

Diabetes mellitus generally referred to as diabetes is reaching epidemic proportions in India and all around the world. The degree of disease and destruction due to diabetes and complications connected with diabetes is enormous, and originated a significant health care burden on both households and society. Deficiency of knowledge about diabetes causes untimely death among the population at large. Thus, developing a technique that should spread awareness about diabetes may affect the people. In this book, a mobile/android application based solution to overcome the lack of awareness about diabetes has been presented. The application uses machine learning techniques to predict risk of readmission to the hospital in diabetics. At the same time, the system also provides knowledge about diabetes and some suggestions on the disease. A comparative analysis of four machine learning (ML) algorithms were performed. The Decision Tree (DT) classifier outperforms amongst the 4 ML algorithms. Hence, DT classifier is used to design the machinery for the mobile application for diabetes risk of readmission prediction using UCI dataset. Due to the lack of knowledge many people even don’t know that they have diabetes, this will lead to a serious problem, as duration of unknown disease increases the risks associated with it also increases. Hospital readmission is a high-priority health care quality measure and target for cost reduction. Reducing readmission rates of diabetic patients have the potential to greatly reduce health care costs while simultaneously improving care. In this book, a novel mobile application based solution for this problem is provided. This mobile app, MobDBRCal (Risk of Readmission in Diabetes) will act as an important tool that can help in predicting the chances of risk of readmission in diabetes and also provides knowledge about this chronic disease.

Shifting Temperance Landscapes: Locating Caste and Gender within the Spatial Politics of Drink in the Madras Presidency

“…In Sowjanya's words, "since Dalits and lower castes do not possess purity of caste or sexuality, their menstruation is not a taboo according to the Brahminical patriarchy." 69 If this is the case, then why would Congress picketers resort to a caste slur that would imply that the menstrual blood of the Adi-Dravida woman was imbued with the worst form of impurity?…”