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 …

Information extraction (IE) is a challenging task, particularly when dealing with highly
heterogeneous data. State-of-the-art data mining technologies struggle to process …

Educational big data analytics and computational intelligence have transformed our
understanding of learning ability and computing power, catalyzing the emergence of …

The spread of Covid-19 misinformation on social media had significant real-world
consequences, and it raised fears among internet users since the pandemic has begun …

Predicting diseases in the early stages is extremely important. By taking advantage of
advances in deep learning and fuzzy logic techniques, a new model is proposed in this …

In the realm of medical data processing, particularly in the diagnosis and monitoring of
cardiac diseases, the analysis of electrocardiogram (ECG) signals represents a critical …

The widespread utilization of social media for information consumption has significantly
exacerbated the problem of information disorder. Recognizing the difficulty people face in …

This book is motivated by the large gap between the black-box nature of deep learning
architectures and the human interpretability of the knowledge models they encode. It is …

Abstract Machine learning (ML) practices such as classification have played a very important
role in classifying diseases in medical science. Since medical science is a sensitive field, the …

The advent of smart healthcare has significantly heightened the importance of computer
technologies in supporting medical diagnosis and treatment. Nevertheless, the challenges …