Blockchain for edge of things: Applications, opportunities, and challenges
In recent years, blockchain networks have attracted significant attention in many research
areas beyond cryptocurrency, one of them being the Edge of Things (EoT) that is enabled by …
areas beyond cryptocurrency, one of them being the Edge of Things (EoT) that is enabled by …
Developments in the detection of diabetic retinopathy: a state-of-the-art review of computer-aided diagnosis and machine learning methods
The exponential increase in the number of diabetics around the world has led to an equally
large increase in the number of diabetic retinopathy (DR) cases which is one of the major …
large increase in the number of diabetic retinopathy (DR) cases which is one of the major …
Early-stage Alzheimer's disease prediction using machine learning models
Alzheimer's disease (AD) is the leading cause of dementia in older adults. There is currently
a lot of interest in applying machine learning to find out metabolic diseases like Alzheimer's …
a lot of interest in applying machine learning to find out metabolic diseases like Alzheimer's …
Recognition of leaf disease using hybrid convolutional neural network by applying feature reduction
Agriculture is crucial to the economic prosperity and development of India. Plant diseases
can have a devastating influence towards food safety and a considerable loss in the …
can have a devastating influence towards food safety and a considerable loss in the …
An effective feature engineering for DNN using hybrid PCA-GWO for intrusion detection in IoMT architecture
The entire computing paradigm is changed due to the technological advancements in
Information and Communication Technology (ICT). Due to these advancements, various …
Information and Communication Technology (ICT). Due to these advancements, various …
Diabetic retinopathy diagnosis from fundus images using stacked generalization of deep models
Diabetic retinopathy (DR) is a diabetes complication that affects the eye and can cause
damage from mild vision problems to complete blindness. It has been observed that the eye …
damage from mild vision problems to complete blindness. It has been observed that the eye …
Enhancement of detection of diabetic retinopathy using Harris hawks optimization with deep learning model
In today's world, diabetic retinopathy is a very severe health issue, which is affecting many
humans of different age groups. Due to the high levels of blood sugar, the minuscule blood …
humans of different age groups. Due to the high levels of blood sugar, the minuscule blood …
InfusedHeart: A novel knowledge-infused learning framework for diagnosis of cardiovascular events
In the undertaken study, we have used a customized dataset termed``Cardiac-200''and the
benchmark dataset``PhysioNet.''which contains 1500 heartbeat acoustic event samples …
benchmark dataset``PhysioNet.''which contains 1500 heartbeat acoustic event samples …
Classification of diabetic retinopathy with feature selection over deep features using nature-inspired wrapper methods
M Canayaz - Applied Soft Computing, 2022 - Elsevier
Diabetic retinopathy (DR) is the most common cause of blindness in middle-aged people. It
shows that an automatic image evaluation system is needed in the diagnosis of this disease …
shows that an automatic image evaluation system is needed in the diagnosis of this disease …
Optimal 5G network slicing using machine learning and deep learning concepts
Network slicing is predetermined to hold up the diversity of emerging applications with
enhanced performance and flexibility requirements in the way of splitting the physical …
enhanced performance and flexibility requirements in the way of splitting the physical …