Machine learning algorithms construct a remarkable contribution to predicting diseases. The
generic purpose of this work is to help the researchers and practitioners to choose …

There are many researchers and data analyst in large companies around the world applied
Machine Learning (ML) in the various study. ML is a subset of Artificial Intelligence (AI) …

Intrusion detection systems is a security technique which analyses network systems and
computer in real time to detect intrusions and manage responsive actions [1]. Signature and …

Background Sickle cell disease (SCD) is the most common inherited blood disorder affecting
millions of people worldwide. Most patients with SCD experience repeated, unpredictable …

Sickle cell disease (SCD) is a common disease among some races around the world,
including Africa, the Caribbean, the East Mediterranean, and the Middle East. Unfortunately …

This research examines the utilization of machine learning to classify medical datasets,
especially to guide sickle cell illness therapy. Numerous studies had shown that machine …

Feature selection plays a crucial role in the domain of machine learning, serving as an
essential mission. Eliminating redundant and irrelevant attributes can enhance the learning …

Machine Learning (ML) is one of the numerous cutting-edge, advanced technology
applications which has grown considerably in popularity over the past decade. It is …

With the technological advancements occurring in the world, particularly in the medical field,
it was important to utilize machine learning algorithms due to their significance in health …

To build an intelligent intrusion detection system, it is essential to have a suitable and high-
quality dataset with a sufficiently large quantity to simulate real-world scenarios. The NSL …