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Emerging research trends in artificial intelligence for cancer diagnostic systems: A comprehensive review
This review article offers a comprehensive analysis of current developments in the
application of machine learning for cancer diagnostic systems. The effectiveness of machine …
application of machine learning for cancer diagnostic systems. The effectiveness of machine …
Data Fusion-based machine learning architecture for intrusion detection
TM Ghazal - Computers, Materials & Continua, 2022 - research.skylineuniversity.ac.ae
In recent years, the infrastructure of Wireless Internet of Sensor Networks (WIoSNs) has
been more complicated owing to developments in the internet and devices' connectivity. To …
been more complicated owing to developments in the internet and devices' connectivity. To …
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 …
Fuzzy‐Based Fusion Model for β‐Thalassemia Carriers Prediction Using Machine Learning Technique
The abnormality of haemoglobin in the human body is the fundamental cause of
thalassemia disease. Thalassemia is considered a common genetic blood condition that has …
thalassemia disease. Thalassemia is considered a common genetic blood condition that has …
Energy demand forecasting using fused machine learning approaches
TM Ghazal - Intelligent Automation & Soft …, 2022 - research.skylineuniversity.ac.ae
The usage of IoT-based smart meter in electric power consumption shows a significant role
in hel** the users to manage and control their electric power consumption. It produces …
in hel** the users to manage and control their electric power consumption. It produces …
Detecting electrocardiogram arrhythmia empowered with weighted federated learning
In this study, a weighted federated learning approach is proposed for electrocardiogram
(ECG) arrhythmia classification. The proposed approach considers the heterogeneity of data …
(ECG) arrhythmia classification. The proposed approach considers the heterogeneity of data …
A deep learning approach to intelligent fruit identification and family classification
The deep learning techniques have been playing an important role in the identification and
classification problems such as diseases in medical science, marketing in the industry …
classification problems such as diseases in medical science, marketing in the industry …
A review on machine learning approaches in identification of pediatric epilepsy
Epilepsy is the second most common neurological disease after Alzheimer. It is a disorder of
the brain which results in recurrent seizures. Though the epilepsy in general is considered …
the brain which results in recurrent seizures. Though the epilepsy in general is considered …
Intelligent Cloud Based Heart Disease Prediction System Empowered with Supervised Machine Learning.
The innovation in technologies related to health facilities today is increasingly hel** to
manage patients with different diseases. The most fatal of these is the issue of heart disease …
manage patients with different diseases. The most fatal of these is the issue of heart disease …
[HTML][HTML] Prediction of hydrogen storage in dibenzyltoluene empowered with machine learning
Hydrogen storage using liquid organic hydrogen carriers (LOHCs) is a promising method.
The data sets for hydrogen storage using dibenzyltoluene (DBT) are considered in this …
The data sets for hydrogen storage using dibenzyltoluene (DBT) are considered in this …