Survey on clinical prediction models for diabetes prediction
Author(s) -
N. Jayanthi,
B. Vijaya Babu,
N. Sambasiva Rao
Publication year - 2017
Publication title -
journal of big data
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.031
H-Index - 35
ISSN - 2196-1115
DOI - 10.1186/s40537-017-0082-7
Subject(s) - computational science and engineering , computer science , predictive modelling , diabetes mellitus , machine learning , data mining , artificial intelligence , data science , medicine , endocrinology
Predictive analytics has gained a lot of reputation in the emerging technology Big data. Predictive analytics is an advanced form of analytics. Predictive analytics goes beyond data mining. A huge amount of medical data is available today regarding the disease, their symptoms, reasons for illness, and their effects on health. But this data is not analysed properly to predict or to study a disease. The aim of this paper is to give a detailed version of predictive models from base to state-of-art, describing various types of predictive models, steps to develop a predictive model, their applications in health care in a broader way and particularly in diabetes.
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