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Several interdisciplinary studies highlight imperfect information as a possible explanation of skill mismatches, which in turn has implications for unemployment and informality rates. Despite information failures and the...

An end-to-end methodology based on deep learning for the detection and localization of microcalcifications in digital mammograms introduces a novel methodology designed for the preprocessing and localization of clusters ...

It is a privilege to present you with this stimulating book, which brings together an exceptional selection of ideas, experiences and reflections resulting from the meeting of a wide range of innovative educators from di...

The communicators’ training is one the fields with more updates due to constant changes faced every year. Therefore, digital native students have competencies developed in an informal way that become a natural bridge t...

We investigated the longitudinal predictors of reading and spelling of words and pseudowords with different syllabic structures in a shallow orthography. Participants were 47 Spanish-speaking children from kindergarten t...

The integration of renewable energy sources into modern power systems is a global priority aimed at reducing carbon emissions, decreasing fossil fuel dependency, and advancing sustainable development goals. In this conte...

Objectives: This study aimed to develop an automated deep learning (DL) system to detect and classify second molar (M2) pathologies associated with impacted third molars (ITMs) on panoramic radiographs. We sought to enha...

Background: The development of accurate artificial intelligence (AI) models for liver cancer diagnosis using contrast-enhanced computed tomography (CT) is often hindered by patient privacy regulations and considerable da...

Background: This study aims to evaluate the effectiveness and efficiency of combined multiple-case teaching (MCT) and narrative medicine teaching (NMT) method compared with lecture-based learning (LBL) in the clinical pr...

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...

Background and Purpose: Deep learning segmentation (DLS) and planning (DLP) models in radiotherapy treatment planning increase consistency and reduce planning time. However, many DL segmentations and plans are manually a...

Objective: The prevalence of adjacent segment disease (ASD) following lumbar surgery is strongly linked to posterior lumbar interbody fusion (PLIF). The goal of this study was to create and validate a composite deep lear...

Dynamic gesture recognition is a core technology for human–computer interaction, yet existing methods face prominent limitations in hand spatial topology modeling, long–short-term temporal feature fusion, and general...

Background: Non-traumatic osteonecrosis of the femoral head (ONFH) can progress to severe osteoarthritis without early intervention. The modified light bulb (MLB) and multiple drilling (MD) techniques aim to preserve the...

Background: The risk of rupture associated with intradural internal carotid artery (ICA) aneurysms warrants considerable attention. We aimed to develop the first machine learning (ML) model that integrates standardized h...

Power transformers are critical components of power systems, and their safe and reliable operation is essential for both industrial and residential applications. Real-time condition monitoring and early fault detection a...

Background From lung cancer and heart disease to rare disorders, research on almost every disease is speeding up. Microscopic cell image analysis is an important area of medical research. As the first step in analysis, s...

Background and purpose: Accurate segmentation of the urethra is crucial for safe focal dose escalated radiotherapy, while prostate zone identification is important for prostate cancer diagnosis. Manual delineations on ma...

Introduction: The advancement of AI-assisted oral disease diagnosis critically relies on the availability of annotated, high-quality datasets and resilient deep learning architectures. Nevertheless, progress in this doma...

الملخص: أهداف البحث: يُعدّ كلٌّ من التعلّم القائم على حلّ المشكلات والتعلّم القائم على العمل الجماعي استراتيجيتين تعليم...

Introduction and aims: This study investigated the synergistic effect of combining 10-methacryloyloxydecyl dihydrogen phosphate (10-MDP) and γ-methacryloxypropyl trimethoxysilane (γ-MPTS) in one primer on bonding to li...

Malignant tumors pose a significant global health challenge. While established screening methods exist, they are largely site-specific, limiting comprehensive prevention. Multi-cancer screening, which detects multiple ca...

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...