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The landscape of higher education (HE) continues to change rapidly with the incorporation of new artificial intelligence (AI) applications like generative artificial intelligence (genAI). These transformations can be att...

Although vaccination remains one of the most impactful interventions in contemporary public health, with consistent and widely documented reductions in morbidity and mortality, the traditional empirical development of va...

Abstract Artificial intelligence (AI) is increasingly used in gastrointestinal endoscopy for polyp detection and classification. However, most AI models are trained on images from multiple video processors, whereas clini...

Background Identifying priority projects in industry–education integration is critical for optimizing policy support and resource allocation. While prior studies have primarily relied on qualitative assessments, there ...

Abstract This study examines the influence of divisor selection on the efficacy of advanced analytical spectrophotometric methods that integrate artificial intelligence (AI), green-chemistry principles, and white-analyti...

No presente estudo examinou-se a associação entre duas dimensões de personalidade, neuroticismo e extroversão, com inteligência emocional (IE), medida por meio de uma escala de Autorrelato. Participaram da pesquisa ...

Abstract Emotional intelligence is widely used to refer to the capacity to perceive, assess, and manage one’s and others’ emotions to attain personal and collective goals. This study aims to identify current and emer...

Abstract Background Non-small-cell lung cancer (NSCLC) exhibits pronounced molecular heterogeneity, and current predictive models rarely incorporate mitochondrial quality-control programs such as mitophagy. We hypothesiz...

With the great developments in optical communication technology and large-scale optical integration technology, it is imperative to realize the traditional functions of polarization processing on an integration platform....

Abstract Fractures are among the most common presentations to emergency and orthopedic services, yet radiograph interpretation remains inconsistent, particularly in resource-limited and off-hours settings. Weakly supervi...

Objective: ‘Values’ of Health Service Managers (HSMs) can be identified by a central organising concept of leadership, which is underpinned by emotional intelligence. Values, whether conscious or not, serve as guidi...

ABSTRACT Influence maximisation (IM) aims to select a small number of nodes that are able to maximise their influence in a network and covers a wide range of applications. Despite numerous attempts to provide effective s...

Abstract BackgroundArtificial intelligence (AI) integrated with point-of-care imaging is a promising approach to expand access in settings with limited specialist availability. However, no systematic review h...

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with strong invasiveness, limited treatment options, and poor prognosis. Its early accurate diagnosis and individualized treatment are major challenges f...

Abstract Metabolic dysfunction-Associated Steatotic Liver Disease (MASLD) affects 30–50% of obese children, yet accurate non-invasive quantification remains challenging. While magnetic resonance imaging-proton density ...

IntroductionWe address moral uncertainty in reinforcement learning (RL) by proposing a framework that integrates multiple ethical theories into decision-making. Existing approaches rely on single moral frameworks or hand...

The agricultural sector contributes significantly to the economic development of nations worldwide. Owing to the population explosion, agriculture must address the complex challenges to meet the growing food demand while...

Background and objectives: The multiple chest x-ray datasets released in the last years have ground-truth labels intended for different computer vision tasks, suggesting that performance in automated chest x-ray interpre...

Aims/objectives: This study aimed to evaluate the performance of leading large language models (LLMs) in orthopedic surgery, with a focus on diagnostic accuracy, radiographic interpretation, subspecialty-specific perform...

In this work, a structured hierarchy of hyperdatasets for Monkeypox image classification is presented, aiming to evaluate the robustness and generalization ability of deep classification models for Mpox detection. A syst...

Digital twins are increasingly used in wireless networks to provide geometry- and channel-aware replicas that support prediction and control, while large language models (LLMs) offer strong instruction-following capabili...

ABSTRACT Analysing learners' facial expressions during learning and exploring their learning processes and emotional changes are of great significance for assisting teachers' teaching and promoting smart education. In co...

Background: Conventional electrocardiography (ECG) analysis faces a persistent dichotomy: Expert-defined features provide interpretability but are limited in capturing latent high-dimensional patterns, whereas deep learn...

The February 2026 issue presents 17 research papers within its regular section, covering a wide range of areas including Artificial Intelligence (AI), Machine Learning (ML), Web and Cloud Technologies, Recommender System...