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Manual Gross Tumor Volume (GTV) delineation for radiotherapy is time‑consuming and prone to inter‑observer variability. Deep Learning (DL)-based auto‑segmentation offers faster and more consistent solutions, but tr...

Abstract The accurate prediction of the deterioration of Continuously Reinforced Concrete Pavement (CRCP) is essential for the effective management of pavements and the maintenance of infrastructure. In this study, a co...

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...

Abstract The Boreal Summer Intraseasonal Oscillation (BSISO) is a prominent tropical intraseasonal variability during summer. It propagates northeastward from the northern Indian Ocean to the western North Pacific and ha...

This study examines the application of artificial intelligence in analyzing and understanding the urban morphology of Zanjan. The primary objective of this research is to propose a machine learning-based framework for th...

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...

Abstract Alzheimer’s disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of accessible early diagnostic methods. Even though it has en...

Abstract Optimizing surgical decisions in breast cancer is critical. Choosing between mastectomy and breast-conserving surgery (BCS) is complex due to heterogeneous pre-operative clinical factors. We developed BrCaM (Bre...

ABSTRACT Background and Aims Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), is transforming healthcare by enabling improved diagnosis, prognosis, and personalized treatments. How...

This article emphasizes the critical importance of public administration effectiveness during a full-scale war, highlighting the capacity of government to respond efficiently to security challenges, maintain public order...

Abstract Background Knee osteoarthritis (OA) is a leading global cause of disability, yet conventional tools lack sensitivity for early detection and precise prognostication. Artificial intelligence (AI) and machine lear...

Selected aspects of methodological developments in socio-economic research are addressed from a conceptual perspective, with outlining the areas of transformations in methodology, and illustrating the feasibilities of it...

Abstract Accurate prediction of compressive strength is important for the efficient design of sustainable concrete incorporating palm oil fuel ash (POFA). This study developed a hybrid artificial neural network model opt...

ABSTRACT Efficient exploration is critical in handling sparse rewards and partial observability in deep reinforcement learning. However, most existing intrinsic reward methods based on novelty rely on single‐step obser...

Abstract Background The research shows the impact of land use forms and population density on the spatial variation of COVID-19 cases and deaths. Selected elements of land use that influence the number of COVID-19 cases ...

Clinical research and real-world observational studies are essential for advancing the diagnosis and treatment of rare diseases, such as inborn errors of immunity/primary immune disorders (IEI/PID). To support efficient ...

Learning correlations from data forms the foundation of today's machine learning (ML) and artificial intelligence research. While contemporary methods enable the automatic discovery of complex patterns, they are prone to...

This study provides a quantitative framework for wellbeing outcome prediction through intentional cognitive pattern alteration. We demonstrated 81.67% accurate prediction of wellbeing states, in a three-level classificat...

Abstract Background Bacterial diseases include any illness caused by bacteria. Bacteria are tiny microorganisms that can only be seen with a microscope. Other types of microorganisms include viruses, fungi, and some para...

"Left Bundle Branch Block (LBBB) diagnosis is crucial for patient stratification and the selection of individuals who are likely to respond to Cardiac Resynchronization Therapy (CRT). The pathophysiological distinction b...

Carbon allowances constitute a foundational component of national carbon emission control frameworks, as they govern the equitable distribution of subsequent allocations and directly shape the overall effectiveness of gr...

ABSTRACT Intrinsic motivation serves as the predominant paradigm of exploration in reinforcement learning. In pursuit of an informative and robust state representation, the behavioural metric groups behaviourally equival...

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...

An accurate intraoperative assessment of tissue perfusion in digestive surgery is critical to prevent complications such as anastomotic leakage, an event in which a surgical connection between organs fails to heal proper...