66 Results Found

Background and Objectives: Integrating large language models (LLMs) such as GPT-4 Turbo into diagnostic imaging faces a significant challenge, with current misdiagnosis rates ranging from 30–50%. This study evaluates how prompt engineering and...

Background: Large language models (LLMs) like GPT-3.5-Turbo and GPT-4 show potential to transform medical diagnostics through their linguistic and analytical capabilities. This study evaluates their diagnostic proficiency using English and German med...

Large Language Models (LLMs) are becoming increasingly integrated into our lives. Hence, it is important to understand the biases present in their outputs in order to avoid perpetuating harmful stereotypes, which originate in our own flawed ways of t...

Assessment is fundamental to programming education; however, it is a labour-intensive and complicated process, especially in extensive learning contexts where it relies significantly on human teachers. This paper presents an automated grading methodo...

With the rising incidence of traffic accidents and growing environmental concerns, the demand for advanced systems to ensure traffic and environmental safety has become increasingly urgent. This paper introduces an automated highway safety management...

In this paper, we introduce an innovative approach to handling the multi-armed bandit (MAB) problem in non-stationary environments, harnessing the predictive power of large language models (LLMs). With the realization that traditional bandit strategi...

This study investigates the efficacy of advanced large language models, specifically GPT-4o, Claude-3.5 Sonnet, and GPT-3.5 Turbo, in detecting software vulnerabilities. Our experiment utilized vulnerable and secure code samples from the NIST Softwar...

The incorporation of artificial intelligence in educational contexts has significantly transformed the support provided to students facing learning difficulties, facilitating both the management of their educational process and their emotions. Additi...

This study investigates the strategic decision-making abilities of large language models (LLMs) via the game of Tic-Tac-Toe, renowned for its straightforward rules and definitive outcomes. We developed a mobile application coupled with web services,...

A modification of the brainstorming process by the application of artificial intelligence (AI) was proposed. Here, we describe the design of the software system “kresilnik”, which enables hybrid work between a human group and AI. The prop...

Background: Systematic reviewers face a growing body of biomedical literature, making early-stage article screening increasingly time-consuming. In this study, we assessed six large language models (LLMs)—OpenHermes, Flan T5, GPT-2, Claude 3 Ha...

Background/Objectives: Falls are the most common adverse in-hospital event, resulting in a considerable social and economic burden on individuals, their families, and the healthcare system. This study aims to develop and implement an automatic coding...

In the product design and manufacturing process, the effective management and representation of system requirements (SRs) are crucial for ensuring product quality and consistency. However, current methods are hindered by document ambiguity, weak requ...

We developed an innovative system that combines Natural Language Understanding (NLU), a curated knowledge base, and the efficient management of a Large Language Model (LLM) to support motivational health coaching. Using Rasa as the core framework, we...

The rise in abusive language on social media is a significant threat to mental health and social cohesion. For Bengali speakers, the need for effective detection is critical. However, current methods fall short in addressing the massive volume of con...

In this study, we conduct a pioneering and comprehensive examination of ChatGPT’s (GPT-3.5 Turbo) capabilities within the realm of Korean Grammatical Error Correction (K-GEC). Given the Korean language’s agglutinative nature and its rich...

Textual emotion recognition (TER) has significant commercial potential since it can be used as an excellent tool to monitor a brand/business reputation, understand customer satisfaction, and personalize recommendations. It is considered a natural lan...

This study evaluates the zero-shot classification performance of eight commercial large language models (LLMs), GPT-4o, GPT-4o Mini, GPT-3.5 Turbo, Claude 3.5 Haiku, Gemini 2.0 Flash, DeepSeek Chat, DeepSeek Reasoner, and Grok, using the CoDA dataset...

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...

In the rapidly evolving domain of conversational agents, the integration of Large Language Models (LLMs) into Chatbot Development Platforms (CDPs) is a significant innovation. This study compares the efficacy of employing generic and fine-tuned GPT-3...

Objective: Patient information materials are sensitive and, if poorly written, can cause misunderstanding. This study evaluated and compared the readability, actionability, and quality of patient education materials on laryngology topics generated by...

This study presents a fine-tuned Large Language Model approach for predicting band gap and stability of transition metal sulfides. Our method processes textual descriptions of crystal structures directly, eliminating the need for complex feature engi...

Traditional methods for assessing urban waterlogging hazards lack real-time efficiency. This study develops a rapid hazard assessment method for urban waterlogging events using social media data and large language models, with the urban waterlogging...

Background/Objectives: This paper aims to assess ChatGPT’s performance in answering European Board of Ophthalmology Diploma (EBOD) examination papers and to compare these results to pass benchmarks and candidate results. Methods: This cross-sec...

This study conducts a comprehensive comparative analysis of six contemporary artificial intelligence models for Python code generation using the HumanEval benchmark. The evaluated models include GPT-3.5 Turbo, GPT-4 Omni, Claude 3.5 Sonnet, Claude 3....

The rapid evolution of large language models, in particular OpenAI’s GPT-3.5-turbo and GPT-4, indicates a growing interest in advanced computational methodologies. This paper proposes a novel approach to synthetic data generation and knowledge...

Background/Objectives: This study aimed to investigate the accuracy of Tumor, Node, Metastasis (TNM) classification based on radiology reports using GPT3.5-turbo (GPT3.5) and the utility of multilingual large language models (LLMs) in both Japanese a...

Prognostics and Health Management (PHM), including fault diagnosis and Remaining Useful Life (RUL) prediction, is critical for ensuring the reliability and efficiency of industrial equipment. However, traditional AI-based methods require extensive ex...

The proliferation of user-generated content in today’s digital landscape has further increased dependence on online reviews as a source for decision-making in the hospitality industry. There has been an increasing interest in automating this de...

The automated transcription of mathematical formulas represents a complex challenge that is of great importance for digital processing and comprehensibility of mathematical content. Consequently, our goal was to analyze state-of-the-art approaches fo...

Software testing ensures the quality and reliability of software products, but manual test case creation is labor-intensive. With the rise of Large Language Models (LLMs), there is growing interest in unit test creation with LLMs. However, effective...

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...

The rapid development of artificial intelligence (AI) and growing reliance on generative AI (GenAI) tools such as ChatGPT and Bing Chat have raised concerns about risks, including privacy violations, bias, and discrimination. AI governance is viewed...

Neural machine translation (NMT) has shown impressive performance when trained on large-scale corpora. However, generic NMT systems have demonstrated poor performance on out-of-domain translation. To mitigate this issue, several domain adaptation met...

Large Language Models (LLMs) are reshaping the landscape of Machine Learning (ML) application development. The emergence of versatile LLMs capable of undertaking a wide array of tasks has reduced the necessity for intensive human involvement in train...

Conversational recommender systems (CRSs) have garnered increasing attention for their ability to provide personalized recommendations through natural language interactions. Although large language models (LLMs) have shown potential in recommendation...

In the intricate field of legal studies, the analysis of court decisions is a cornerstone for the effective functioning of the judicial system. The ability to predict court outcomes helps judges during the decision-making process and equips lawyers w...

The automation of educational and instructional assessment plays a crucial role in enhancing the quality of teaching management. In physics education, calculation problems with intricate problem-solving ideas pose challenges to the intelligent gradin...

Programming education traditionally requires extensive manual assessment of student assignments, which is both time-consuming and resource-intensive for instructors. Recent advances in large language models (LLMs) open opportunities for automating th...

This paper presents an exploration into the capabilities of an adaptive PID controller within the realm of truck platooning operations, situating the inquiry within the context of Cognitive Radio and AI-enhanced 5G and Beyond 5G (B5G) networks. We de...

This study presents the development of an AI-powered chatbot designed to facilitate accurate and efficient retrieval of information from the FDA drug labeling documents. Leveraging OpenAI’s GPT-3.5-turbo model within a controlled, document-grou...

This study aimed to develop a large language model (LLM) chatbot for radiation therapy education and compare the performance of portable document format (PDF)- and webpage-based question-and-answer (Q&A) chatbots. An LLM chatbot was created using...

Asbestos, consisting of six natural mineral fibrous silicate phases, was widely utilized in industrial development during the 20th century and has left a global legacy of health, environmental, and regulatory challenges. Its remarkable properties (e....

Advancements in natural language processing (NLP), particularly Large Language Models (LLMs), have greatly improved how we access knowledge. However, in critical domains like biomedicine, challenges like hallucinations—where language models gen...

Text comprehension is an essential skill in today’s information-rich world, and self-explanation practice helps students improve their understanding of complex texts. This study was centered on leveraging open-source Large Language Models (LLMs...

X-ray photoelectron spectroscopy (XPS) remains a fundamental technique in materials science, offering invaluable insights into the chemical states and electronic structure of a material. However, the interpretation of XPS spectra can be complex, requ...

Chain-of-Thought (CoT) prompting has demonstrated strong effectiveness in improving the reasoning capabilities of Large Language Models (LLMs). However, existing CoT optimization approaches still lack systematic mechanisms for evaluating and refining...

Generative artificial intelligence (genAI) shows promising results in clinical practice. This study compared a GPT-4-turbo virtual assistant with physicians from Italy, France, Spain, and Portugal on medical knowledge derived from national exams whil...

The increasing frequency and destructiveness of natural disasters necessitate scalable, transparent, and timely analytical frameworks for risk reduction. Traditional disaster datasets—curated by intergovernmental bodies such as EM-DAT and UNDRR...

In the emerging field of computational gastronomy, aligning culinary practices with scientifically supported nutritional goals is increasingly important. This study explores how large language models (LLMs) can be applied to optimize ingredient subst...