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VOL. 11, ISSUE 2 (2025)
A comprehensive review of deep ensemble learning techniques for medical disease diagnosis
Authors
Kulkarni Usha Bhimrao, Dr. Sanjay Kumar
Abstract
The fast development of artificial intelligence
in healthcare has made a considerable difference in the system of disease diagnosis
and prediction. Deep ensemble learning has become one of the powerful techniques
that have been able to combine several machine learning and deep learning models
to enhance diagnostic accuracy, robustness, and generalization. The present review
paper is a thorough analysis of the deep ensemble learning methods used in medical
disease diagnosis. It critically compares the traditional classifiers, such as Support
Vector Machines (SVM), Naive Bayes and K-Nearest Neighbors (KNN) as well as state
of the art deep learning architectures, such as Convolutional Neural Networks (CNNs),
ResNet, VGG16 and MobileNetV2. The paper identifies some of the major issues in
medical data analysis, including class imbalance, noisy and heterogeneous data,
and high dimensionality. The special attention is paid to Synthetic Minority Oversampling
Technique (SMOTE) and noise filtering techniques that improve the quality of the
data and the performance of the model. Moreover, the effectiveness of ensemble strategies
like bagging, boosting, and stacking are discussed in terms of their success in
enhancing predictive performance in complex medical data. Results indicate that
deep ensemble learning models are more accurate, sensitive and reliable compared
to single-model approaches, especially in critical applications, like cancer detection,
cardiovascular disease prediction and medical imaging analysis. This review also
points out gaps in research and outlines the direction of the research in the future
to develop efficient, interpretable and scalable diagnostic systems. In general,
deep ensemble learning has great potential as an intelligent clinical-decision-support
system to diagnose the disease at an early and accurate stage.
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Pages:31-37
How to cite this article:
Kulkarni Usha Bhimrao, Dr. Sanjay Kumar "A comprehensive review of deep ensemble learning techniques for medical disease diagnosis". International Journal of Research in Advanced Engineering and Technology, Vol 11, Issue 2, 2025, Pages 31-37
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