A Review on Microstrip Patch Antenna Performance Improvement Techniques on Various Applications
Volume-3 | Issue-3
A Review on Finding Efficient Approach to Detect Customer Emotion Analysis using Deep Learning Analysis
Volume-3 | Issue-2
A Comparative Analysis of Prediction of Student Results Using Decision Trees and Random Forest
Volume-4 | Issue-3
Study of Security Mechanisms to Create a Secure Cloud in a Virtual Environment with the Support of Cloud Service Providers
Volume-2 | Issue-3
Construction of Black Box to Detect the Location of Road Mishap in Remote Area in the IoT Domain
Volume-3 | Issue-2
Fault Diagnosis in Hybrid Renewable Energy Sources with Machine Learning Approach
Volume-3 | Issue-3
Secure and Optimized Cloud-Based Cyber-Physical Systems with Memory-Aware Scheduling Scheme
Volume-2 | Issue-3
Stochastic Geometry and Performance Analysis of Large Scale Wireless Networks
Volume-3 | Issue-3
Computer Vision on IOT Based Patient Preference Management System
Volume-2 | Issue-2
Fake News Detection using Data Mining Techniques
Volume-3 | Issue-4
A Review on Microstrip Patch Antenna Performance Improvement Techniques on Various Applications
Volume-3 | Issue-3
Fake News Detection using Data Mining Techniques
Volume-3 | Issue-4
A Comparative Analysis of Prediction of Student Results Using Decision Trees and Random Forest
Volume-4 | Issue-3
Speedy Detection Module for Abandoned Belongings in Airport Using Improved Image Processing Technique
Volume-3 | Issue-4
Deployment of Artificial Intelligence with Bootstrapped Meta-Learning in Cyber Security
Volume-4 | Issue-3
Design an Early Detection and Classification for Diabetic Retinopathy by Deep Feature Extraction based Convolution Neural Network
Volume-3 | Issue-2
Design of an Intelligent Approach on Capsule Networks to Detect Forged Images
Volume-3 | Issue-3
Future Challenges of the Internet of Things in the Health Care Domain - An Overview
Volume-3 | Issue-4
Construction of Black Box to Detect the Location of Road Mishap in Remote Area in the IoT Domain
Volume-3 | Issue-2
A Review on Finding Efficient Approach to Detect Customer Emotion Analysis using Deep Learning Analysis
Volume-3 | Issue-2
Volume - 4 | Issue - 4 | december 2022
Published
24 January, 2023
This study provides a bibliometric review of deep learning applications in diabetes between 2018 and 2022, with an analysis of the 2201 publications. This review highlights the influential aspects of deep learning in diabetes research from a bibliometric perspective. Deep learning has drawn significant interest from researchers, particularly those working in diabetes. Two well-known databases: Web of Science and Scopus, each of which having its own data format, are combined into a single format using the R programming language in R Studio, and the duplicates are removed. The Bibliometrix package is used to conduct quantitative analysis, which includes highlighting the primary journals, the works that have been referenced the most, the authors, nations, and institutions that have produced the most, as well as keyword clustering, paper split into sub-periods to track theme progression, and top trend analysis. The findings demonstrate a notable increase in publications since 2018. A plethora of studies are conducted on the practical applications of deep learning to treat diabetes, which is dramatically rising. IEEE Access, Scientific Reports, and Computers in Biology and Medicine are the top three most relevant journals. China is most productive and its publications are highly cited, while the USA comes second. Accuracy, atrial fibrillation, and heart infarction have recently been the hot topics. The most frequently used words are human, article, and diabetes mellitus. The findings help academics better understand the study area in this related field, which is one of the hottest research fields in Artificial Intelligence.
KeywordsBibliometrics Diabetes Deep Learning Scient metrics Trends
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