Convergence of blockchain and artificial intelligence in IoT network for the sustainable smart city

S Singh, PK Sharma, B Yoon, M Shojafar… - Sustainable cities and …, 2020 - Elsevier
In the digital era, the smart city can become an intelligent society by utilizing advances in
emerging technologies. Specifically, the rapid adoption of blockchain technology has led a …

[HTML][HTML] Machine learning and artificial intelligence based Diabetes Mellitus detection and self-management: A systematic review

J Chaki, ST Ganesh, SK Cidham… - Journal of King Saud …, 2022 - Elsevier
Diabetes Mellitus (DM) is a condition induced by unregulated diabetes that may lead to multi-
organ failure in patients. Thanks to advances in machine learning and artificial intelligence …

[HTML][HTML] Overcoming nonlinear dynamics in diabetic retinopathy classification: a robust AI-based model with chaotic swarm intelligence optimization and recurrent long …

YB Özçelik, A Altan - Fractal and Fractional, 2023 - mdpi.com
Diabetic retinopathy (DR), which is seen in approximately one-third of diabetes patients
worldwide, leads to irreversible vision loss and even blindness if not diagnosed and treated …

Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey

S Bhattacharya, PKR Maddikunta, QV Pham… - Sustainable cities and …, 2021 - Elsevier
Since December 2019, the coronavirus disease (COVID-19) outbreak has caused many
death cases and affected all sectors of human life. With gradual progression of time, COVID …

Analysis of dimensionality reduction techniques on big data

GT Reddy, MPK Reddy, K Lakshmanna, R Kaluri… - Ieee …, 2020 - ieeexplore.ieee.org
Due to digitization, a huge volume of data is being generated across several sectors such as
healthcare, production, sales, IoT devices, Web, organizations. Machine learning algorithms …

An ensemble machine learning approach through effective feature extraction to classify fake news

S Hakak, M Alazab, S Khan, TR Gadekallu… - Future Generation …, 2021 - Elsevier
There are numerous channels available such as social media, blogs, websites, etc., through
which people can easily access the news. It is due to the availability of these platforms that …

[HTML][HTML] Diabetic retinopathy detection using principal component analysis multi-label feature extraction and classification

TM Usman, YK Saheed, D Ignace, A Nsang - International Journal of …, 2023 - Elsevier
Diabetic Retinopathy (DR) is the most common cause of eyesight loss that affects millions of
people worldwide. Although there are recognized screening procedures for detecting the …

A novel PCA–whale optimization-based deep neural network model for classification of tomato plant diseases using GPU

TR Gadekallu, DS Rajput, MPK Reddy… - Journal of Real-Time …, 2021 - Springer
The human population is growing at a very rapid scale. With this progressive growth, it is
extremely important to ensure that healthy food is available for the survival of the inhabitants …

Deep neural networks to predict diabetic retinopathy

TR Gadekallu, N Khare, S Bhattacharya… - Journal of Ambient …, 2023 - Springer
Diabetic retinopathy is a prominent cause of blindness among elderly people and has
become a global medical problem over the last few decades. There are several scientific …

A critical review on diagnosis of diabetic retinopathy using machine learning and deep learning

D Das, SK Biswas, S Bandyopadhyay - Multimedia Tools and Applications, 2022 - Springer
Diabetic Retinopathy (DR) is a health condition caused due to Diabetes Mellitus (DM). It
causes vision problems and blindness due to disfigurement of human retina. According to …