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Introduction and aims: Oral and maxillofacial surgery (OMFS) produces complex clinical data, while artificial intelligence (AI) applications in this field remain limited despite great potential. This study aimed to map t...

In this study, a novel Quantum Self-Attention Neural Network for Multi-Model Aerial Image Classification (QSANN-MAIC) is proposed. The objective of this paper is to develop a high-performance learning framework capable o...

Lung diseases such as pneumonia, tuberculosis, COVID-19, and lung cancer remain significant global health challenges that demand rapid and accurate diagnosis to improve patient outcomes. This study proposes NASNet-ViT, a...

This study explains how consumers form attitudes toward sustainable fashion line extensions by integrating Brand Extension Theory (BET) with the Theory of Planned Behavior (TPB). Using survey data from 786 consumers in P...

Colorimetric assays offer a low-cost, accessible means of diagnostic testing but often suffer from subjective interpretation and variability caused by inconsistent imaging conditions. To address these challenges, we pres...

Objectives: Deep learning networks have achieved significant progress in caries diagnosis, but automated localization and numbering of carious teeth in cone-beam computed tomography (CBCT) images remain underexplored. Th...