Terrorist group's forums remain a threat for all web users. It stills need to be inspired with
algorithms to detect the informative contents. In this paper, we investigate most discussed topics …

Hate speech has become a hot research topic in the area of natural language processing (NLP)
due to the tremendous increase in the usage of social media platforms like Instagram, …

To effectively manage the great amount of data on Arabic web pages and to enable the
classification of relevant information are very important research problems. Studies on sentiment …

Background Obesity and diabetes are two chronic metabolic diseases whose prevalence is
increasing at an alarming rate globally. A close association between obesity, diabetes, and …

BACKGROUND: Diabetic foot ulcers (DFU) are a critical complication of diabetes mellitus (DM)
affecting life quality and significantly impacting healthcare resources. OBJECTIVE: …

Clustering is the method employed to group Web pages containing related information into
clusters, which facilitates the allocation of relevant information. Clustering performance is …

Objectives: To evaluate the clinical presentations and immunohistochemical (IHC) properties
of gastrointestinal stromal tumors (GISTs) and to compare them to internationally published …

The main aim of the present study was to investigate the presence of Differential Item Functioning
(DIF) using a latent class (LC) analysis approach. Particularly, we examined potential …

Introduction Primary hepatic neuroendocrine tumours (PHNETs) are a rare form of hepatic
neoplasms, and it is difficult to differentiate them from common hepatic malignancies in …

Sentiment analysis plays a crucial role in understanding public opinion and social media
trends. It involves analyzing the emotional tone and polarity of a given text. When applied to …