Prediction model using SMOTE, genetic algorithm and decision tree (PMSGD) for classification of diabetes mellitus
Diabetes mellitus is a well-known chronic disease that diminishes the insulin producing
capability of the human body. This results in high blood sugar level which might lead to …
capability of the human body. This results in high blood sugar level which might lead to …
A review on prediction of diabetes using machine learning and data mining classification techniques
Machine learning (ML) and data mining (DM) techniques have grown in popularity among
researchers and scientists in various fields. The healthcare industry could not be an …
researchers and scientists in various fields. The healthcare industry could not be an …
Diabetes detection using deep learning techniques with oversampling and feature augmentation
MT García-Ordás, C Benavides… - Computer Methods and …, 2021 - Elsevier
Background and objective: Diabetes is a chronic pathology which is affecting more and
more people over the years. It gives rise to a large number of deaths each year …
more people over the years. It gives rise to a large number of deaths each year …
Diabetes detection based on machine learning and deep learning approaches
The increasing number of diabetes individuals in the globe has alarmed the medical sector
to seek alternatives to improve their medical technologies. Machine learning and deep …
to seek alternatives to improve their medical technologies. Machine learning and deep …
Early and accurate prediction of diabetics based on FCBF feature selection and SMOTE
A Kishor, C Chakraborty - … Journal of System Assurance Engineering and …, 2024 - Springer
Diabetes is a chronic hyperglycemic disorder. Every year hundreds of millions of people
around the world have diabetes. The presence of irrelevant features and an imbalanced …
around the world have diabetes. The presence of irrelevant features and an imbalanced …
A new nearest neighbor-based framework for diabetes detection
Diabetes is one of the deadliest and costliest diseases. Today, automatic diabetes detection
systems are primarily developed using deep learning (DL) approaches, which give high …
systems are primarily developed using deep learning (DL) approaches, which give high …
Solutions Using Machine Learning for Diabetes
Diabetes mellitus, a chronic disease that has a significant influence on human lives, families,
and communities globally, has reached alarming levels and is therefore a leading economic …
and communities globally, has reached alarming levels and is therefore a leading economic …
A fuzzy rule-based system for classification of diabetes
Diabetes is a fatal disease that currently has no treatment. However, early diagnosis of
diabetes aids patients to start timely treatment and thus reduces or eliminates the risk of …
diabetes aids patients to start timely treatment and thus reduces or eliminates the risk of …
Bio-inspired machine learning approach to Type 2 Diabetes Detection
Type 2 diabetes is a common life-changing disease that has been growing rapidly in recent
years. According to the World Health Organization, approximately 90% of patients with …
years. According to the World Health Organization, approximately 90% of patients with …
Electrochemical dual signal sensing platform for the simultaneous determination of dopamine, uric acid and glucose based on copper and cerium bimetallic carbon …
R Li, H Liang, M Zhu, M Lai, S Wang, H Zhang, H Ye… - …, 2021 - Elsevier
A highly sensitive electrochemical sensor for the simultaneous dual signal determination of
dopamine (DA), uric acid (UA) and glucose (Glu) has been obtained using nanocomposites …
dopamine (DA), uric acid (UA) and glucose (Glu) has been obtained using nanocomposites …