[HTML][HTML] 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 …
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] Retinal image analysis for diabetes-based eye disease detection using deep learning
Diabetic patients are at the risk of developing different eye diseases ie, diabetic retinopathy
(DR), diabetic macular edema (DME) and glaucoma. DR is an eye disease that harms the …
(DR), diabetic macular edema (DME) and glaucoma. DR is an eye disease that harms the …
Microvascular complications in type-2 diabetes: a review of statistical techniques and machine learning models
Abstract Type 2 Diabetes (T2D) has become a serious concern as it contributes to 90% of
the total diabetic population. The high glucose levels in diabetic patients result in damage to …
the total diabetic population. The high glucose levels in diabetic patients result in damage to …
[HTML][HTML] Deep neural network with moth search optimization algorithm based detection and classification of diabetic retinopathy images
In recent days, progressive rate of diabetic retinopathy (DR) becomes high and it is needed
to develop an automated model for effective diagnosis of DR. This paper presents a new …
to develop an automated model for effective diagnosis of DR. This paper presents a new …
Optimal Deep Neural Network model based multimodality fused medical image classification
Medical image fusion and classification has been utilized to get valuable significant data
multimodality medical image data. The fundamental commitment of this paper is to extricate …
multimodality medical image data. The fundamental commitment of this paper is to extricate …
An efficient coding network based feature extraction with support vector machine based classification model for CT lung images
AS Oliver, M Anuradha, JJ Justus… - Journal of Medical …, 2020 - ingentaconnect.com
Lung cancer is a serious illness affects people all over the globe. To increase the survival
rate of patients affected by lung cancer, in advance recognition of lung cancer with effective …
rate of patients affected by lung cancer, in advance recognition of lung cancer with effective …
Diabetic retinopathy lesions detection using faster-RCNN from retinal images
Diabetic Retinopathy is an eye disease that damages the retina which can cause vision loss.
Early detection of DR is needed because the disease shows little signs in its initial stage due …
Early detection of DR is needed because the disease shows little signs in its initial stage due …
[PDF][PDF] Cyber security in cloud using blowfish encryption
S Hussaini - Int. J. Inf. Technol.(IJIT), 2020 - academia.edu
Due to the inexorable notoriety of ubiquitous mobile devices and cloud processing, storing
of data (for example photographs, recordings, messages, and texts) in the cloud has turned …
of data (for example photographs, recordings, messages, and texts) in the cloud has turned …
[HTML][HTML] Efficient sampling-based energy function evaluation for ensemble optimization using simulated annealing
In this study, we attempted to develop a method for accelerating parameter optimization of
an object detector ensemble over large image datasets by using simulated annealing. We …
an object detector ensemble over large image datasets by using simulated annealing. We …