Niharika Gupta¹, Baijnath Kaushik¹, Mohammad Khalid Imam Rahmani^2,*, Saima Anwar Lashari^2,*

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 347-366, 2023, DOI:10.32604/cmc.2023.038864

Abstract Diabetes is one of the fastest-growing human diseases worldwide and poses a significant threat to the population’s longer lives. Early prediction of diabetes is crucial to taking precautionary steps to avoid or delay its onset. In this study, we proposed a Deep Dense Layer Neural Network (DDLNN) for diabetes prediction using a dataset with 768 instances and nine variables. We also applied a combination of classical machine learning (ML) algorithms and ensemble learning algorithms for the effective prediction of the disease. The classical ML algorithms used were Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbor (KNN),… More >

R. Rajkamal^1,*, Anitha Karthi², Xiao-Zhi Gao³

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2013-2033, 2022, DOI:10.32604/cmc.2022.027142

Abstract Diabetes is increasing commonly in people’s daily life and represents an extraordinary threat to human well-being. Machine Learning (ML) in the healthcare industry has recently made headlines. Several ML models are developed around different datasets for diabetic prediction. It is essential for ML models to predict diabetes accurately. Highly informative features of the dataset are vital to determine the capability factors of the model in the prediction of diabetes. Feature engineering (FE) is the way of taking forward in yielding highly informative features. Pima Indian Diabetes Dataset (PIDD) is used in this work, and the impact of informative features in… More >

Altyeb Altaher Taha^*, Sharaf Jameel Malebary

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6089-6105, 2022, DOI:10.32604/cmc.2022.023848

Abstract Diabetes is a chronic health condition that impairs the body's ability to convert food to energy, recognized by persistently high levels of blood glucose. Undiagnosed diabetes can cause many complications, including retinopathy, nephropathy, neuropathy, and other vascular disorders. Machine learning methods can be very useful for disease identification, prediction, and treatment. This paper proposes a new ensemble learning approach for type 2 diabetes prediction based on a hybrid meta-classifier of fuzzy clustering and logistic regression. The proposed approach consists of two levels. First, a base-learner comprising six machine learning algorithms is utilized for predicting diabetes. Second, a hybrid meta-learner that… More >

Milos Mravik¹, T. Vetriselvi², K. Venkatachalam^3,*, Marko Sarac¹, Nebojsa Bacanin¹, Sasa Adamovic¹

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 457-471, 2022, DOI:10.32604/cmc.2022.020687

Abstract At present, the prevalence of diabetes is increasing because the human body cannot metabolize the glucose level. Accurate prediction of diabetes patients is an important research area. Many researchers have proposed techniques to predict this disease through data mining and machine learning methods. In prediction, feature selection is a key concept in preprocessing. Thus, the features that are relevant to the disease are used for prediction. This condition improves the prediction accuracy. Selecting the right features in the whole feature set is a complicated process, and many researchers are concentrating on it to produce a predictive model with high accuracy.… More >

Shabib Aftab^1,2, Saad Alanazi³, Munir Ahmad¹, Muhammad Adnan Khan^4,*, Areej Fatima⁵, Nouh Sabri Elmitwally^3,6

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1341-1357, 2021, DOI:10.32604/cmc.2021.016814

Abstract Diabetes mellitus, generally known as diabetes, is one of the most common diseases worldwide. It is a metabolic disease characterized by insulin deficiency, or glucose (blood sugar) levels that exceed 200 mg/dL (11.1 ml/L) for prolonged periods, and may lead to death if left uncontrolled by medication or insulin injections. Diabetes is categorized into two main types—type 1 and type 2—both of which feature glucose levels above “normal,” defined as 140 mg/dL. Diabetes is triggered by malfunction of the pancreas, which releases insulin, a natural hormone responsible for controlling glucose levels in blood cells. Diagnosis and comprehensive analysis of this… More >