Deep neuro-fuzzy systems (DNFSs) have been successfully applied to real-world problems
using the efficient learning process of deep neural networks (DNNs) and reasoning aptitude …

Pressure Injuries (PI) are one of the most common health conditions in the United States.
Most acute or long-term care patients are at risk of develo** PI. Machine Learning (ML) …

Airway segmentation is crucial for the examination, diagnosis, and prognosis of lung
diseases, while its manual delineation is unduly burdensome. To alleviate this time …

In recent years, deep learning has evolved as a rapidly growing and stimulating field of
machine learning and has redefined state-of-the-art performances in a variety of …

Abstract Deep Neuro-Fuzzy System has been successfully employed in various
applications. But, the model faces two issues:(i) dataset with many features exponentially …

In this article, we propose a novel composite learning framework for interval type-2 (IT2)
fuzzy logic systems (FLSs) to train regression models with a high accuracy performance and …

Cardiotocography data uncertainty is a critical task for the classification in biomedical field.
Constructing good and efficient classifier via machine learning algorithms is necessary to …

Automatic lung organ segmentation on computerized tomography images is crucial for lung
disease diagnosis. However, the unlimited voxel values and class imbalance of lung organs …

Ordered Weighted Averaging (OWA) operators have been integrated in Convolutional
Neural Networks (CNNs) for image classification through the OWA layer. This layer lets the …

In bridge maintenance, risk assessment is critical to prioritizing project work to minimize
related risks and costs. However, the conventional method of risk assessment relies heavily …