An ensemble approach to predict early-stage diabetes risk using machine learning: An empirical study
Diabetes is a long-lasting disease triggered by expanded sugar levels in human blood and
can affect various organs if left untreated. It contributes to heart disease, kidney issues …
can affect various organs if left untreated. It contributes to heart disease, kidney issues …
eDiaPredict: an ensemble-based framework for diabetes prediction
Medical systems incorporate modern computational intelligence in healthcare. Machine
learning techniques are applied to predict the onset and reoccurrence of the disease …
learning techniques are applied to predict the onset and reoccurrence of the disease …
Data-driven machine-learning methods for diabetes risk prediction
Diabetes mellitus is a chronic condition characterized by a disturbance in the metabolism of
carbohydrates, fats and proteins. The most characteristic disorder in all forms of diabetes is …
carbohydrates, fats and proteins. The most characteristic disorder in all forms of diabetes is …
Early prediction of diabetes using an ensemble of machine learning models
Diabetes is one of the most rapidly spreading diseases in the world, resulting in an array of
significant complications, including cardiovascular disease, kidney failure, diabetic …
significant complications, including cardiovascular disease, kidney failure, diabetic …
[HTML][HTML] Prediction of diabetes using logistic regression and ensemble techniques
P Rajendra, S Latifi - Computer Methods and Programs in Biomedicine …, 2021 - Elsevier
Background Logistic regression is a classification model in machine learning, extensively
used in clinical analysis. It uses probabilistic estimations which helps in understanding the …
used in clinical analysis. It uses probabilistic estimations which helps in understanding the …
[HTML][HTML] Peer reviewed: building risk prediction models for type 2 diabetes using machine learning techniques
Methods We analyzed cross-sectional data on 138,146 participants, including 20,467 with
type 2 diabetes, from the 2014 Behavioral Risk Factor Surveillance System. We built several …
type 2 diabetes, from the 2014 Behavioral Risk Factor Surveillance System. We built several …
A review on current advances in machine learning based diabetes prediction
V Jaiswal, A Negi, T Pal - Primary Care Diabetes, 2021 - Elsevier
Diabetes is a metabolic disorder comprising of high glucose level in blood over a prolonged
period in the body as it is not capable of using it properly. The severe complications …
period in the body as it is not capable of using it properly. The severe complications …
Predicting diabetes mellitus with machine learning techniques
Diabetes mellitus is a chronic disease characterized by hyperglycemia. It may cause many
complications. According to the growing morbidity in recent years, in 2040, the world's …
complications. According to the growing morbidity in recent years, in 2040, the world's …
Machine learning models for data-driven prediction of diabetes by lifestyle type
Y Qin, J Wu, W Xiao, K Wang, A Huang, B Liu… - International journal of …, 2022 - mdpi.com
The prevalence of diabetes has been increasing in recent years, and previous research has
found that machine-learning models are good diabetes prediction tools. The purpose of this …
found that machine-learning models are good diabetes prediction tools. The purpose of this …
Predicting the onset of type 2 diabetes using wide and deep learning with electronic health records
Objective Diabetes is responsible for considerable morbidity, healthcare utilisation and
mortality in both developed and developing countries. Currently, methods of treating …
mortality in both developed and developing countries. Currently, methods of treating …