Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T

Gastroesophageal reflux disease (GERD) is a prevalent clinical condition, that affects millions of individuals worldwide. Objective: To assess the level of soluble HLA-E (sHLA-E) as a biomarker in the diagnosis and immunopathogenesis of GERD patients. Methods: The case-control prospective study included 40 GERD patients who were consulted at the Gastroenterology Unit of AlKindy Teaching Hospital, as along with 40 healthy control subjects. The study period extended from January 2023 to May 2024. Blood was drawn from both groups and serum was separated to assesssHLA-E using a sandwich enzyme-linked immunosorbent assay (ELISA) kit. Results: There was a statistically significant difference in sHLA-E levels between GERD patients and healthy cont

An automatic text summarization system mimics how humans summarize by picking the most ‎significant sentences in a source text. However, the complexities of the Arabic language have become ‎challenging to obtain information quickly and effectively. The main disadvantage of the ‎traditional approaches is that they are strictly constrained (especially for the Arabic language) by the ‎accuracy of sentence feature ‎functions, weighting schemes, ‎and similarity calculations. On the other hand, the meta-heuristic search approaches have a feature tha

KE Sharquie, MM Al-Waiz, AA Al-Nuaimy, Saudi medical journal, 2005 - Cited by 8