IEEE

Automated Ensemble Multimodal Machine Learning for Healthcare

Abstract: The application of machine learning in medicine and healthcare has led to the creation of numerous diagnostic and prognostic models. However, despite their success, current approaches ...
Scientific Research Publishing

Diabetic Retinopathy Severity Classification Using Data Fusion and Ensemble Transfer Learning ()

Diabetic retinopathy is a serious concern for people dealing with diabetes. Detecting diabetic retinopathy poses significant challenges, requiring skilled professionals, extensive manual image ...
Scientific Research Publishing

Das, S., Venugopal, D. and Shiva, S. (2024) A Holistic Approach for Detecting DDoS Attacks by Using Ensemble Unsupervised Machine Learning.

ABSTRACT: The use of machine learning algorithms to identify characteristics in Distributed Denial of Service (DDoS) attacks has emerged as a powerful approach in cybersecurity. DDoS attacks, which ...
IEEE

Dynamical Targeted Ensemble Learning for Streaming Data With Concept Drift

Abstract: Concept drift is an important characteristic and inevitable difficult problem in streaming data mining. Ensemble learning is commonly used to deal with concept drift. However, most ensemble ...
News Medical

Ensemble deep learning models enhance early diagnosis of Alzheimer's disease using neuroimaging data

EDL combines the outputs of several machine learning (ML) models to enhance their generalization performance. The traditional approach to building an ensemble uses deep neural networks (DNNs) in a ...