Object tracking: A survey
The goal of this article is to review the state-of-the-art tracking methods, classify them into
different categories, and identify new trends. Object tracking, in general, is a challenging …
different categories, and identify new trends. Object tracking, in general, is a challenging …
[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 …
Analysis of diabetes mellitus for early prediction using optimal features selection
Diabetes is a chronic disease or group of metabolic disease where a person suffers from an
extended level of blood glucose in the body, which is either the insulin production is …
extended level of blood glucose in the body, which is either the insulin production is …
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 …
Convolutional recurrent neural networks for glucose prediction
Control of blood glucose is essential for diabetes management. Current digital therapeutic
approaches for subjects with type 1 diabetes mellitus such as the artificial pancreas and …
approaches for subjects with type 1 diabetes mellitus such as the artificial pancreas and …
Evaluating trust prediction and confusion matrix measures for web services ranking
To accurately rank various web services can be a very challenging task depending on the
evaluation criteria used, however, it can play an important role in performing a better …
evaluation criteria used, however, it can play an important role in performing a better …
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 …
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 …
disease that endangered human life in all parts of the world. The late stage of Type-II DM …
An analytical method for diseases prediction using machine learning techniques
The use of medical datasets has attracted the attention of researchers worldwide. Data
mining techniques have been widely used in develo** decision support systems for …
mining techniques have been widely used in develo** decision support systems for …