[HTML][HTML] Design of biosensor for synchronized identification of diabetes using deep learning
A Armghan, J Logeshwaran, SM Sutharshan… - Results in …, 2023 - Elsevier
A highly sensitive biosensor for the synchronized identification of diabetes is designed using
a deep learning approach. The biosensor is built on a cutting-edge platform that combines …
a deep learning approach. The biosensor is built on a cutting-edge platform that combines …
[HTML][HTML] Diabetes detection using deep learning algorithms
Diabetes is a metabolic disease affecting a multitude of people worldwide. Its incidence
rates are increasing alarmingly every year. If untreated, diabetes-related complications in …
rates are increasing alarmingly every year. If untreated, diabetes-related complications in …
A deep learning approach based on convolutional LSTM for detecting diabetes
Diabetes is a chronic disease that occurs when the pancreas does not generate sufficient
insulin or the body cannot effectively utilize the produced insulin. If it remains unidentified …
insulin or the body cannot effectively utilize the produced insulin. If it remains unidentified …
[HTML][HTML] An intelligent diabetic patient tracking system based on machine learning for E-health applications
Background: Continuous surveillance helps people with diabetes live better lives. A wide
range of technologies, including the Internet of Things (IoT), modern communications, and …
range of technologies, including the Internet of Things (IoT), modern communications, and …
[HTML][HTML] Iot and cloud computing in health-care: A new wearable device and cloud-based deep learning algorithm for monitoring of diabetes
Diabetes is a chronic disease that can affect human health negatively when the glucose
levels in the blood are elevated over the creatin range called hyperglycemia. The current …
levels in the blood are elevated over the creatin range called hyperglycemia. The current …
Diabetes detection using machine learning classification methods
N Abdulhadi, A Al-Mousa - 2021 International Conference on …, 2021 - ieeexplore.ieee.org
The main objective of this research is to predict the possible presence of diabetes-
specifically in females-at an early stage using different machine learning techniques. Early …
specifically in females-at an early stage using different machine learning techniques. Early …
[HTML][HTML] Machine learning models for non-invasive glucose measurement: towards diabetes management in smart healthcare
The patients of diabetes require to observe and control their glycemic profile through
continuous glucose level monitoring. The blood glucose measurement is possible through …
continuous glucose level monitoring. The blood glucose measurement is possible through …
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 …
[HTML][HTML] 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 …
A comprehensive exploration to the machine learning techniques for diabetes identification
Diabetes mellitus, known as diabetes, is a group of metabolic disorders and has affected
hundreds of millions of people. The detection of diabetes is of great importance, concerning …
hundreds of millions of people. The detection of diabetes is of great importance, concerning …