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Use and performance of machine learning models for type 2 diabetes prediction in community settings: A systematic review and meta-analysis
Objective We aimed to identify machine learning (ML) models for type 2 diabetes (T2DM)
prediction in community settings and determine their predictive performance. Method …
prediction in community settings and determine their predictive performance. Method …
A survey on event detection approaches for sensor based IoT
Over the period, two significant advancements ie shrinking of the sensor size and improved
communication capability, lead the sensor-based internet-of-things (SBIoT) to mature …
communication capability, lead the sensor-based internet-of-things (SBIoT) to mature …
Architecting smart city digital twins: Combined semantic model and machine learning approach
This work was motivated by the premise that next-generation smart city systems will be
enabled by widespread adoption of sensing and communication technologies deeply …
enabled by widespread adoption of sensing and communication technologies deeply …
Interpretable filter based convolutional neural network (IF-CNN) for glucose prediction and classification using PD-SS algorithm
Diabetes mellitus is a disease commonly called Diabetes. Diabetes is among the most
frequent diseases globally. This disease affects internationally with different ailments and …
frequent diseases globally. This disease affects internationally with different ailments and …
RETRACTED ARTICLE: A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment
Abstract Internet of Things (IoT) and smart medical devices have improved the healthcare
systems by enabling remote monitoring and screening of the patients' health conditions …
systems by enabling remote monitoring and screening of the patients' health conditions …
An AI-based intelligent system for healthcare analysis using Ridge-Adaline Stochastic Gradient Descent Classifier
Recent technological advancements in information and communication technologies
introduced smart ways of handling various aspects of life. Smart devices and applications …
introduced smart ways of handling various aspects of life. Smart devices and applications …
The impact of data pre-processing techniques and dimensionality reduction on the accuracy of machine learning
Data pre-processing is considered as the core stage in machine learning and data mining.
Normalization, discretization, and dimensionality reduction are well-known techniques in …
Normalization, discretization, and dimensionality reduction are well-known techniques in …
A novel enhanced hybrid clinical decision support system for accurate breast cancer prediction
Feature selection is one of the crucial data preprocessing techniques for improving the
performance of machine learning (ML) models. Recently, metaheuristic feature selection …
performance of machine learning (ML) models. Recently, metaheuristic feature selection …
FBSED based automatic diagnosis of COVID-19 using X-ray and CT images
This work introduces the Fourier-Bessel series expansion-based decomposition (FBSED)
method, which is an implementation of the wavelet packet decomposition approach in the …
method, which is an implementation of the wavelet packet decomposition approach in the …
Study of data-driven thermal sensation prediction model as a function of local body skin temperatures in a built environment
Current thermal/sensation models primarily rely on predefined formulas or empirically
defined recommendations, but fail to consider each individual's physiological characteristics …
defined recommendations, but fail to consider each individual's physiological characteristics …