Despite the benefits of artificial intelligence-assisted language learning (AIALL) for students and teachers, the scientific literature in this field remains relatively scarce, especially regarding the perceptions of language teachers. This paper aim...
Background/Objectives: Trichoscopy is an important diagnostic tool for hair and scalp disorders, but it requires significant expertise. Publicly available large language models (LLMs) are becoming more popular among both physicians and patients, yet...
This article is a discursive and equivalence-generating study of the use of the multilingual property as a narrative transmission mechanism in audiovisual texts. Specific functions can be constructed and different events and aspects of the plot can b...
How to objectively evaluate the effect of different vectorization models in measuring similarity between patents is a fundamental issue, which can help to select high-performance vectorization models to support advanced patent services. Based on the...
Background: Social Communication Disorder (SCD), introduced in the DSM-5, is distinguished from Autism Spectrum Disorder (ASD) by the absence of restricted and repetitive behaviors or interests (RRBIs). Aim: To compare the adaptive, sensory, communic...
Human language comprehension relies on predictive processing; however, the computational mechanisms underlying this phenomenon remain unclear. This study investigates these mechanisms using large language models (LLMs), specifically GPT-3.5-turbo and...
In recent years, there has been an increase in the prevalence of comorbidity between ASD and epilepsy in the pediatric population. Children with ASD and epilepsy often exhibit greater impairments in executive functions such as cognitive flexibility,...
Recently, transformer-based pretrained language models have demonstrated stellar performance in natural language understanding (NLU) tasks. For example, bidirectional encoder representations from transformers (BERT) have achieved outstanding performa...
This paper examines the Khotanese tradition in the political and cultural history of the Tarim Basin in the first millennium CE by foregrounding its role as an active facilitator within a multicultural and continually transforming geopolitical enviro...
In this comparative study, we investigated different influential factors of mobile-assisted language learning (MALL) for improving productive and receptive language learning skills. To do this, 100 scientific research papers were selected from the to...
Objectives: This study aimed to evaluate the performance of four AI models, (GPT-5, GPT-4, Microsoft Copilot, and Google Gemini), in detecting medication errors through pediatric case scenarios. Methods: A total of 60 pediatric cases were analyzed fo...
Fred Kuwornu’s 18 Ius Soli (2011) intervenes in debates on citizenship, migration, and national identity in Italy by presenting the testimonies of eighteen young people born or raised in Italy to immigrant parents who remain excluded from autom...
Objective: A considerable number of gliomas require resection via direct electrical stimulation (DES) during awake craniotomy. Likewise, the feasibility of resecting language-eloquent gliomas purely based on navigated repetitive transcranial magnetic...
In 1802, Friedrich Hölderlin experienced his first mental breakdown, which was followed by a second one in 1805. On 15th September 1806, he was admitted to the clinic of Johann Heinrich Ferdinand von Autenrieth in Tübingen who addressed H&o...
This study examines the characteristics of abstract language use in gifted preschool children during natural free-play activities and compares them with those of typically developing children. The aim is to enhance our awareness of characteristics of...
This paper explores the emerging security risks in Large Language Models (LLMs) through a comparative study of jailbreaking techniques. These adversarial methods exploit linguistic and alignment weaknesses in LLMs to bypass content safeguards and gen...
The primary goal of this study is to predict and analyze customer trust in e-commerce by leveraging neural computation within large language models (LLMs) alongside configurational approaches. We employ LLMs to predict trust levels based on customer...
Background/Objectives: Periodontitis is a highly prevalent chronic disease requiring accurate diagnosis for effective treatment planning. Artificial intelligence (AI) has emerged as a potential tool to support clinical decision-making. This study aim...
Large language models (LLMs), including ChatGPT, Gemini, and DeepSeek, are increasingly used in medicine; however, their performance across multiple clinically relevant domains remains incompletely understood. This cross-sectional comparative study e...
Background/Objectives: Migraine is a common and disabling neurological disorder, and many individuals increasingly seek information online. With the growing use of large language models (LLMs), such as ChatGPT, for patient education, concerns have em...
The paper discusses the implementation of a bilingual education language policy in the context of endangered indigenous sign language—Icelandic Sign Language (íslenskt táknmál, ÍTM). Unlike other indigenous endangered languages (e.g., Sámi), or other...
Accurate data analysis is an important part of data-driven financial audits. Given the increased data availability and various systems from which audit files are generated, RCSFI provides a way for standardization on behalf of analysis. This research...
Background: Large Language Models (LLMs) such as ChatGPT, Claude, and Gemini are being increasingly adopted in medicine; however, their reliability in cardiology remains underexplored. Purpose of the study: To compare the performance of three general...
Recent advances in artificial intelligence have expanded the use of large language models (LLMs) beyond speech-based applications and increased interest in their potential roles in dental education. However, evidence regarding LLM performance in post...
In an era where fake news detection has become a pressing issue due to its profound impacts on public opinion, democracy, and social trust, accurately identifying and classifying false information is a critical challenge. In this study, the effective...
In today’s rapidly evolving digital landscape, customer reviews play a crucial role in shaping the reputation and success of hotels. Accurately analyzing and classifying the sentiment of these reviews offers valuable insights into customer sati...
Grammatical error correction (GEC) has become increasingly important for enhancing the quality of OCR-scanned texts. This small-scale study explores the application of Large Language Models (LLMs) for GEC in German children’s literature, a genr...
Designing effective temporal modeling strategies for video-based sign language recognition (SLR) remains challenging, particularly in low-resource settings where the behavior of modern architectures is not fully understood. In this study, we present...
Background: Large language models (LLMs) are increasingly used by patients for obtaining medical information; however, concerns remain regarding their clinical safety, reliability, and appropriateness of patient guidance. Evidence evaluating LLM perf...
Background/Objectives: Secondary hypertension (SH) requires complex diagnostic reasoning and guideline-based management, posing substantial challenges for artificial intelligence–driven clinical decision-support systems. This study aimed to com...
Background: Virtual coaching can help people adopt new healthful behaviors by encouraging them to set specific goals and helping them review their progress. One challenge in creating such systems is analyzing clients’ statements about their act...
This study presents a comparative analysis of several multimodal large language models (LLMs) for no-reference image quality assessment, with a particular focus on images containing authentic distortions. We evaluate three models developed by OpenAI...
Background: Infection prevention and control (IPC) in hospitals relies heavily on infection control nurses (ICNs) who manage complex consultations to prevent and control infections. This study evaluated large language models (LLMs) as artificial inte...
Background/Objectives: Skeletal dysplasias are a heterogeneous group of rare genetic disorders with diverse and overlapping clinical presentations, posing diagnostic challenges even for experienced clinicians. With the increasing availability of arti...
Large Language Models (LLMs) combined with visual foundation models have demonstrated significant advancements, achieving intelligence levels comparable to human capabilities. This study analyzes the latest Multimodal LLMs (MLLMs), including Multimod...
Although a wealth of research has examined the predictors influencing the discrepancies between individual-set and parent-set career goals (DBIPCG), investigations grounded in collectivist cultural perspectives remain relatively scarce. Within collec...
The use of large language models (LLMs) to automate the generation of medical case-based multiple-choice questions (MCQs) is increasing, but their accuracy, reliability, and educational validity are still not well understood. This study in a comparat...
Background/Objectives: To evaluate the numerical agreement and variability between large language model (LLM)-generated surgical dosage recommendations and expert surgical planning in strabismus surgery under controlled conditions. Methods: This retr...
Accurate identification of Alzheimer’s disease (AD)-related cellular characteristics from microscopy images is essential for understanding neurodegenerative mechanisms at the cellular level. While most computational approaches focus on macrosco...
This study analyzes 194,151 tweets from the 2021 German federal election using sentiment analysis and statistical techniques to examine social media’s role in shaping group emotions, voters’ emotional expression and derogatory speech towa...
Objective: This study aimed to compare the accuracy of two large language models (LLMs)—ChatGPT (version 3.5) and Google Gemini (formerly Bard)—in answering dental caries-related multiple-choice questions (MCQs) using a simulated student...
Background: Large language models (LLMs) have shown potential for clinical decision support. However, the diagnostic performance of newly released frontier models—including GPT-5 and Gemini 2.5 Pro—in gastroenterology remains insufficient...
Background and Objectives: General-purpose multimodal large language models (MLLMs) can interpret radiographic images, but their classification performance across orthodontic tasks remains uncertain. This study compared the classification performance...
Background/Objectives: Large language models (LLMs) are increasingly investigated in dentistry and oral and maxillofacial surgery, but comparative evidence regarding specialist-level response quality, clinical content, and potential safety concerns r...
Human communication has long relied on visual media for interaction, and is facilitated by electronic devices that access visual data. Traditionally, this exchange was unidirectional, constrained to text-based queries. However, advancements in human&...
Risk identification is a critical concern in the construction industry. In recent years, there has been a growing trend of applying artificial intelligence (AI) tools to detect risks from unstructured data sources such as news articles, social media,...
Among human activities, coal mining and the combustion of fossil fuels are important sources of mercury in the environment. Research on mercury pollution in coal mining areas and surrounding cities, especially in densely populated areas, has always b...
Background: Legal capacity assessment requires multidisciplinary evaluation integrating cognitive, functional, neurological, psychiatric, and medico-legal information. Although large language models (LLMs) have shown promise in structured clinical re...
Large language models (LLMs) have shown great potential in solving complex mathematical problems, but their performance in university-level mathematics is still underexplored. This study provides a systematic evaluation of eleven state-of-the-art LLM...
Intrusion detection in industrial cyber-physical systems is constrained by small labelled-attack corpora and by the subtler signal of physical-process attacks compared with classical IT-network intrusions, motivating renewed interest in foundation-mo...
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