To maintain network security, Intrusion Detection System (IDS) is needed to detect anomaly
and attack. Designing proper IDS requires accurate model. This paper proposes a model …

The standard method for diagnosing varices by upper endoscopy is invasive, costly, and has
many drawbacks. To overcome these drawbacks, this study aims to build a predictive …

The high-dimensional nature of medical data frequently results in suboptimal performance of
machine learning models. Applying feature selection before classification is necessary to …

In recent years, heart disease has become a reason for high mortality rate, and data mining
has also gained attention in the medical domain. Predicting this disease in its initial stage …

A metaheuristic-based data optimization algorithm with machine learning-based feature
extraction and classification architectures is proposed. The medical data collected from …

Abstract Child Drawing Development Optimization is a recently developed metaheuristic
algorithm that has been demonstrated to perform well on multiple benchmark tests. In this …

Heart attacks are one of the foremost causes of death in the world. While doctors can carry
out multiple tests to diagnose it, it may go undetected for a long time which can prove fatal …

Background: Heart disease prediction model helps physicians to identify patients who are at
high risk of developing heart disease and target prevention strategies accordingly. These …

Deep learning and machine learning researchers must overcome the difficulty of big data
analytics. One such technique for big data analytics is distributed systems, which allows data …

Outpatient clinics globally grapple with the uncertainty of patient wait times, a critical factor
affecting patient satisfaction. Extended waiting periods are often perceived as a hindrance to …