A systematic review on metaheuristic optimization techniques for feature selections in disease diagnosis: open issues and challenges
There is a need for some techniques to solve various problems in today's computing world.
Metaheuristic algorithms are one of the techniques which are capable of providing practical …
Metaheuristic algorithms are one of the techniques which are capable of providing practical …
Artificial Intelligence approaches for Predicting Hypertension Diseases: Open Challenges and Research Issues
Despite improved therapies and decades of research over the last century, hypertension
remained the world's leading avoidable cause of death. Machine learning (ML) is a subfield …
remained the world's leading avoidable cause of death. Machine learning (ML) is a subfield …
Machine learning and deep learning based time series prediction and forecasting of ten nations' COVID-19 pandemic
In the paper, the authors investigated and predicted the future environmental circumstances
of a COVID-19 to minimize its effects using artificial intelligence techniques. The …
of a COVID-19 to minimize its effects using artificial intelligence techniques. The …
Artificial intelligence techniques for the detections of congenital diseases: challenges and research perspectives
Congenital infections, disorders, or diseases occur when pregnant women get infected with
an organism that further enters into their placenta and fetus after entering their bloodstream …
an organism that further enters into their placenta and fetus after entering their bloodstream …
A Detailed Analysis of Many Different Artificial Intelligence-Based Healthcare Systems
The healthcare industry is one of the world's fastest growing, and the impact of artificial
intelligence (AI) is already being felt. AI is changing the way healthcare is delivered, from …
intelligence (AI) is already being felt. AI is changing the way healthcare is delivered, from …
Machine Learning Based Intrusion Detection System
R Udayakumar, D Balakrishnan… - 2023 3rd …, 2023 - ieeexplore.ieee.org
In today's digital landscape, the increasing frequency and sophistication of cyberattacks
have highlighted the necessity for robust intrusion detection systems (IDS) to safe-guard …
have highlighted the necessity for robust intrusion detection systems (IDS) to safe-guard …
A Machine Learning Methodology for Detecting SQL Injection Attacks
In today's environment, we all rely on web applications. The number of web application
users is growing by the day. Most organizations use databases to hold data about their …
users is growing by the day. Most organizations use databases to hold data about their …
[HTML][HTML] Deep neural network model for enhancing disease prediction using auto encoder based broad learning
Abstract Bioinformatics and Healthcare Integration Disease prediction models have been
revolutionized by Big Data. These models, which make use of extensive medical data …
revolutionized by Big Data. These models, which make use of extensive medical data …
A Predictive Analysis of Autism Spectrum Disorder Using Ensemble Techniques of Machine Learning
R Udayakumar, K Sreekumar… - 2023 3rd …, 2023 - ieeexplore.ieee.org
Autism spectrum disorder (ASD) is a complicated neurological illness characterised by
impairments in social interaction, communication, and restricted behaviour. In order to …
impairments in social interaction, communication, and restricted behaviour. In order to …
Machine Learning-Based Diagnosis and Detection of Liver Cancer: An Approach Enhancement
One of the most important organs in our body is the liver, yet liver cancer incidence has been
sharply rising in recent years, primarily as a result of poor lifestyles. In order to accurately …
sharply rising in recent years, primarily as a result of poor lifestyles. In order to accurately …