[HTML][HTML] Machine learning and data mining methods in diabetes research
The remarkable advances in biotechnology and health sciences have led to a significant
production of data, such as high throughput genetic data and clinical information, generated …
production of data, such as high throughput genetic data and clinical information, generated …
[HTML][HTML] Comparative anatomization of data mining and fuzzy logic techniques used in diabetes prognosis
Diabetes is an ailment in which glucose level increase in at high rates in blood due to body's
inability to metabolize it. This happens when body does not produce sufficient amount of …
inability to metabolize it. This happens when body does not produce sufficient amount of …
EAGA-MLP—an enhanced and adaptive hybrid classification model for diabetes diagnosis
Disease diagnosis is a critical task which needs to be done with extreme precision. In recent
times, medical data mining is gaining popularity in complex healthcare problems based …
times, medical data mining is gaining popularity in complex healthcare problems based …
A fusion-based machine learning approach for the prediction of the onset of diabetes
A growing portfolio of research has been reported on the use of machine learning-based
architectures and models in the domain of healthcare. The development of data-driven …
architectures and models in the domain of healthcare. The development of data-driven …
Intelligent machine learning approach for effective recognition of diabetes in E-healthcare using clinical data
Significant attention has been paid to the accurate detection of diabetes. It is a big challenge
for the research community to develop a diagnosis system to detect diabetes in a successful …
for the research community to develop a diagnosis system to detect diabetes in a successful …
Variants of Artificial Bee Colony algorithm and its applications in medical image processing
Abstract The Artificial Bee Colony (ABC) technique is a highly effective method of
optimization inspired by the behavior of bees. Notably, the importance of the ABC algorithm …
optimization inspired by the behavior of bees. Notably, the importance of the ABC algorithm …
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 …
Stacking-based multi-objective evolutionary ensemble framework for prediction of diabetes mellitus
Diabetes mellitus (DM) is a combination of metabolic disorders characterized by elevated
blood glucose levels over a prolonged duration. Undiagnosed DM can give rise to a host of …
blood glucose levels over a prolonged duration. Undiagnosed DM can give rise to a host of …
Neural network classifier optimization using differential evolution with global information and back propagation algorithm for clinical datasets
Abstract A Computer-Aided Diagnostic (CAD) system that uses Artificial Neural Network
(ANN) trained by drawing in the relative advantages of Differential Evolution (DE), Particle …
(ANN) trained by drawing in the relative advantages of Differential Evolution (DE), Particle …
Artificial intelligence applications for friction stir welding: A review
Advances in artificial intelligence (AI) techniques that can be used for different purposes
have enabled it to be used in many different industrial applications. These are mainly used …
have enabled it to be used in many different industrial applications. These are mainly used …