Novel class probability features for optimizing network attack detection with machine learning

A Raza, K Munir, MS Almutairi, R Sehar - IEEE Access, 2023 - ieeexplore.ieee.org
Network attacks refer to malicious activities exploiting computer network vulnerabilities to
compromise security, disrupt operations, or gain unauthorized access to sensitive …

An Explainable Artificial Intelligence Model Proposed for the Prediction of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and the Identification of Distinctive …

FH Yagin, A Alkhateeb, A Raza, NA Samee… - Diagnostics, 2023 - mdpi.com
Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex
and debilitating illness with a significant global prevalence, affecting over 65 million …

Blockchain and Machine Learning in Internet of Vehicles: Applications, Challenges, and Opportunities

M Zamanirafe, P Mansourian… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
The Internet of Vehicles (IoV) has emerged as a promising technology for transforming
transportation systems by leveraging intelligent services and data-driven decision-making …

A Proposed Explainable Artificial Intelligence-Based Machine Learning Model for Discriminative Metabolites for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

FH Yagin, A Alkhateeb, A Raza, NA Samee… - 2023 - preprints.org
Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex
and debilitating disease with a significant global prevalence of over 65 million individuals. It …

Predicting the Conversion from Clinically Isolated Syndrome to Multiple Sclerosis in Mexican Mestizo Patients Using Gaussian Naive Bayes Classifier: A Prospective …

NK Yulinda - International Journal of Artificial Intelligence in …, 2024 - jurnal.yoctobrain.org
This study explores the application of the Gaussian Naive Bayes (GNB) classifier to predict
the conversion from Clinically Isolated Syndrome (CIS) to Multiple Sclerosis (MS) among …