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 …
An intelligent fuzzy inference rule‐based expert recommendation system for predictive diabetes diagnosis
P Nagaraj, P Deepalakshmi - International Journal of Imaging …, 2022 - Wiley Online Library
Diabetes is one of the most common and hazardous diseases, which can affect almost every
organ in the body. Diagnosis of diabetes requires determining all vital parameters related to …
organ in the body. Diagnosis of diabetes requires determining all vital parameters related to …
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 …
[PDF][PDF] Developing a recognition system for classifying covid-19 using a convolutional neural network algorithm
FW Alsaade, THH Aldhyani… - Computers, Materials & …, 2021 - cdn.techscience.cn
The COVID-19 pandemic poses an additional serious public health threat due to little or no
pre-existing human immunity, and developing a system to identify COVID-19 in its early …
pre-existing human immunity, and developing a system to identify COVID-19 in its early …
Diabetic sensorimotor polyneuropathy severity classification using adaptive neuro fuzzy inference system
F Haque, MBI Reaz, MEH Chowdhury… - IEEE …, 2021 - ieeexplore.ieee.org
Diabetic sensorimotor polyneuropathy (DSPN) is an early indicator for non-healing diabetic
wounds and diabetic foot ulcers, which account for one of the most common complications of …
wounds and diabetic foot ulcers, which account for one of the most common complications of …
Medical decision making via the arithmetic of generalized triangular fuzzy numbers
Background: When patient (s) approach to a medical expert to explain their problems, they
often explain their conditions through vague linguistic expression [1]. Medical expert needs …
often explain their conditions through vague linguistic expression [1]. Medical expert needs …
An Ensemble Models for the Prediction of Sickle Cell Disease from Erythrocytes Smears
INTRODUCTION: The human blood as a collection of tissues containing Red Blood Cells
(RBCs), circular in shape and acting as an oxygen carrier, are frequently deformed by …
(RBCs), circular in shape and acting as an oxygen carrier, are frequently deformed by …
A new intelligent approach for effective recognition of diabetes in the IoT e-healthcare environment
A significant attention has been made to the accurate detection of diabetes which is a big
challenge for the research community to develop a diagnosis system to detect diabetes in a …
challenge for the research community to develop a diagnosis system to detect diabetes in a …
Different Machine Learning Algorithms Involved in Glucose Monitoring to Prevent Diabetes Complications and Enhanced Diabetes Mellitus Management
Diabetes mellitus (DM) is a group of metabolic disorders resulting from dysregulation of
blood glucose (BG). Hence, it may lead to various vascular and neural complications …
blood glucose (BG). Hence, it may lead to various vascular and neural complications …
[PDF][PDF] A Fusion-Based Machine Learning Approach for the Prediction of the Onset of Diabetes. Healthcare 2021, 9, 1393
MW Nadeem, HG Goh, V Ponnusamy, I Andonovic… - 2021 - academia.edu
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 …