Novel binary logistic regression model based on feature transformation of XGBoost for type 2 Diabetes Mellitus prediction in healthcare systems

Y Wu, Q Zhang, Y Hu, K Sun-Woo, X Zhang… - Future Generation …, 2022 - Elsevier
The rapidly increasing incidence of Diabetes Mellitus (DM) has shown that DM is a serious
disease that endangered human life in all parts of the world. The late stage of Type-II DM …

Prediction of type 2 diabetes risk and its effect evaluation based on the XGBoost model

L Wang, X Wang, A Chen, X Jin, H Che - Healthcare, 2020 - mdpi.com
In view of the harm of diabetes to the population, we have introduced an ensemble learning
algorithm—EXtreme Gradient Boosting (XGBoost) to predict the risk of type 2 diabetes and …

Efficient prediction of early-stage diabetes using XGBoost classifier with random forest feature selection technique

S Gündoğdu - Multimedia Tools and Applications, 2023 - Springer
Diabetes is one of the most common and serious diseases affecting human health. Early
diagnosis and treatment are vital to prevent or delay complications related to diabetes. An …

Machine learning approach for diabetes detection using fine-tuned XGBoost algorithm

A Maulana, FR Faisal, TR Noviandy… - Infolitika Journal of …, 2023 - heca-analitika.com
Diabetes is a chronic condition characterized by elevated blood glucose levels which leads
to organ dysfunction and an increased risk of premature death. The global prevalence of …

A risk prediction model for type 2 diabetes based on weighted feature selection of random forest and xgboost ensemble classifier

Z Xu, Z Wang - 2019 eleventh international conference on …, 2019 - ieeexplore.ieee.org
Type 2 diabetes mellitus is a severe chronic disease threatening human health and has a
high incidence worldwide. People need to use effective prediction model to diagnose and …

[HTML][HTML] A robust predictive diagnosis model for diabetes mellitus using Shapley-incorporated machine learning algorithms

CJ Ejiyi, Z Qin, J Amos, MB Ejiyi, A Nnani, TU Ejiyi… - Healthcare …, 2023 - Elsevier
With the rapid advancement and integration of Artificial Intelligence (AI) in medicine, the
need for new developments and accuracy in Machine Learning (ML) models and algorithms …

Analysis of prediction accuracy of diabetes using classifier and hybrid machine learning techniques

S Barik, S Mohanty, S Mohanty, D Singh - Intelligent and Cloud …, 2021 - Springer
In the past few years, the growth of diabetes among people became exponential. A health
report tells that about 347 million of world populations are affected by diabetes. Diabetes not …

An ensemble learning approach for diabetes prediction using boosting techniques

SM Ganie, PKD Pramanik, M Bashir Malik… - Frontiers in …, 2023 - frontiersin.org
Introduction: Diabetes is considered one of the leading healthcare concerns affecting
millions worldwide. Taking appropriate action at the earliest stages of the disease depends …

Early prediction of diabetes using an ensemble of machine learning models

A Dutta, MK Hasan, M Ahmad, MA Awal… - International Journal of …, 2022 - mdpi.com
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 …

Diabetes prediction using machine learning and explainable AI techniques

I Tasin, TU Nabil, S Islam… - Healthcare Technology …, 2023 - Wiley Online Library
Globally, diabetes affects 537 million people, making it the deadliest and the most common
non‐communicable disease. Many factors can cause a person to get affected by diabetes …