Deep learning for diabetic retinopathy analysis: a review, research challenges, and future directions
Deep learning (DL) enables the creation of computational models comprising multiple
processing layers that learn data representations at multiple levels of abstraction. In the …
processing layers that learn data representations at multiple levels of abstraction. In the …
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 …
COVID-19 patient health prediction using boosted random forest algorithm
Integration of artificial intelligence (AI) techniques in wireless infrastructure, real-time
collection, and processing of end-user devices is now in high demand. It is now superlative …
collection, and processing of end-user devices is now in high demand. It is now superlative …
Modified U-net architecture for segmentation of skin lesion
Dermoscopy images can be classified more accurately if skin lesions or nodules are
segmented. Because of their fuzzy borders, irregular boundaries, inter-and intra-class …
segmented. Because of their fuzzy borders, irregular boundaries, inter-and intra-class …
Optimal feature selection-based medical image classification using deep learning model in internet of medical things
Internet of Medical Things (IoMT) is the collection of medical devices and related
applications which link the healthcare IT systems through online computer networks. In the …
applications which link the healthcare IT systems through online computer networks. In the …
[HTML][HTML] A building energy consumption prediction model based on rough set theory and deep learning algorithms
L Lei, W Chen, B Wu, C Chen, W Liu - Energy and Buildings, 2021 - Elsevier
The efficient and accurate prediction of building energy consumption can improve the
management of power systems. In this paper, the rough set theory was used to reduce the …
management of power systems. In this paper, the rough set theory was used to reduce the …
Deep learning based an automated skin lesion segmentation and intelligent classification model
Abstract Internet of Medical Things (IoMT) includes interconnected sensors, wearable
devices, medical devices, and clinical systems. At the same time, skin cancer is a commonly …
devices, medical devices, and clinical systems. At the same time, skin cancer is a commonly …
Severity classification of diabetic retinopathy using an ensemble learning algorithm through analyzing retinal images
Diabetic Retinopathy (DR) refers to the damages endured by the retina as an effect of
diabetes. DR has become a severe health concern worldwide, as the number of diabetes …
diabetes. DR has become a severe health concern worldwide, as the number of diabetes …
Automated detection and diagnosis of diabetic retinopathy: A comprehensive survey
V Lakshminarayanan, H Kheradfallah, A Sarkar… - Journal of …, 2021 - mdpi.com
Diabetic Retinopathy (DR) is a leading cause of vision loss in the world. In the past few
years, artificial intelligence (AI) based approaches have been used to detect and grade DR …
years, artificial intelligence (AI) based approaches have been used to detect and grade DR …
Explainable framework for Glaucoma diagnosis by image processing and convolutional neural network synergy: analysis with doctor evaluation
Glaucoma causes blindness in long-time untreated cases. So, its early diagnosis is very
important. Moving from that, there have been lots of Deep Learning oriented studies to …
important. Moving from that, there have been lots of Deep Learning oriented studies to …