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BackgroundReducing under-5 mortality remains a global health priority. Large language models (LLMs) are increasingly used by the public to access medical information. However, current evidence evaluating LLMs’ performa...

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...

Abstract Risk of bias assessment is a crucial step in evidence synthesis. The traditionally adopted tool, however, is complex, resource-intensive, and unreliable. While prior investigations have focused on whether Large ...

BackgroundDigital tools are reshaping public health education and training, yet evidence on whether large language models (LLMs) can generate specialist ophthalmic teaching materials remains limited. High myopia (HM), a ...

IntroductionLarge language models (LLMs) show great promise as tools for assisting scientific peer review, but their agreement with human experts in quantitative assessment of academic content needs further investigation...

IntroductionLarge language models (LLMs) may support clinical reasoning, yet real-world outpatient studies integrating structured clinical data with chest radiographs (CXRs) remain limited. We compared three LLMs for pul...

In the field of autonomous vehicles (AVs), accurately discerning commander intent and executing linguistic commands within a visual context presents a significant challenge. This paper introduces a sophisticated encoder-...

This study examines the potential impact of Large Language Models (LLMs) on the Ukrainian labor market. For the first time, it attempts to estimate the share of employees that can be replaced by generative AI technology ...

Abstract Efficient management and optimal allocation of urban public sports facilities represents a critical challenge in modernizing public sports service governance. Current approaches to facility utilization assessmen...

Abstract This study introduces an intelligent, large language model (LLM)–driven feedback system designed to assess and enhance students’ programming tasks through semantic comparison and pedagogically contextualized...

Large language models (LLMs) have gained significant prominence in language processing, demonstrating remarkable performance across a wide range of tasks. Recently, LLMs have been explored in various scientific fields be...

With the rapid growth of electronic health records, medical imaging, and high-throughput omics data, precision oncology faces increasing demands for cross-modal information integration and complex clinical decision suppo...

Abstract Objective This feasibility study aimed to assess the potential of freely available large language models (LLMs) to support clinical decision-making in obstetrics. Methods Five fictional obstetric patient cases, ...

ABSTRACT As a government‐regulated public service, traffic signal control (TSC) requires reliable and transparent decision‐making. However, existing deep reinforcement learning (DRL) methods, despite improvements in ...

Abstract Background Organizing free-text patient data into a structured format is labor-intensive and time-consuming. This study aims to evaluate the effectiveness of a fine-tuned lightweight language model in structurin...

ABSTRACT To enable autonomous operations in complex industrial environments, this paper proposes retrieval‐augmented generation with large language models for robotic operations (RAGLRO), a robotic framework specifical...

Novel innovations in large language models (LLMs) have demonstrated their ability to generate and analyze literary texts. As a result of intricate semantic layers, metaphors, polyphony, and nonlinear narrative structures...

Background Large language models (LLMs) have demonstrated promising capabilities in medical diagnostic reasoning, yet their performance in specialized clinical domains such as rheumatology remains incompletely characteri...

Reducing embodied carbon in the built environment requires reliable methods to assess structural materials, particularly steel, one of the most carbon-intensive. While environmental product declarations (EPDs) provide st...

Abstract We propose a method that enables large language models (LLMs) to control embodied agents through the generation of control policies that directly map continuous observation vectors to continuous action vectors. ...

Abstract BackgroundMultimodal large language models (MLLMs) capable of integrating visual and textual information represent a promising advancement for clinical applications requiring image interpretation. Wo...

Abstract Ultrasound reporting remains a manual, time-consuming process prone to errors and variability. We present UltraReporter, a compact 8B-parameter LLM pipeline that converts real-time spoken cues into structured ul...

Abstract Large language models are beginning to appear in civil engineering practice, yet their advice often reflects generalized narratives rather than local evidence. This perspective introduces a governance audit fram...