Academic Articles & Research Papers

Prompting Strategies for Readability Alignment Between User-Generated Ophthalmology Questions and Large Language Model Answers: Comparative Evaluation Study.

Influence in the caption: how mega influencers use language in sponsored Instagram posts

Background/IntroductionThe success of influencer marketers' posts on social media often hinges on the influencer's ability to resonate with their audience through the language that they use. By leveraging their unique language cues and comm...

Few-shot learning for automated content analysis: Efficient coding of arguments and claims in the debate on arms deliveries to Ukraine

Pre-trained language models (PLM) based on transformer neural networks developed in the field of natural language processing (NLP) offer great opportunities to improve automatic content analysis in communication science, especially for the ...

Revenue-sensitive evaluation of AI-assisted ICD-10-CM coding and human-AI collaboration under dual DRG payment systems

Abstract Automated ICD-10-CM coding is critical for hospital reimbursement under Diagnosis-Related Group (DRG) payment systems, yet standard metrics weight all errors equally. This study evaluated 11 models on MIMIC-IV under heterogeneous c...

Nanomaterial-based therapeutic strategies for systemic autoimmune rheumatic diseases: from molecular mechanisms to preclinical translation.

Spatial and single-cell insights into the prostate cancer microenvironment: overcoming immunotherapy resistance through multidimensional strategies.

Politeness research: Key trajectories and their applicability in intercultural communication

With the plethora of studies on politeness in general and linguistic politeness in particular, it is difficult for those who want to apply the theoretical findings to authentic language data, to find a roadmap to theoretical framework on wh...

Using 311 data to develop an algorithm to identify urban blight for public health improvement.

The growth of administrative data made available publicly, often in near-real time, offers new opportunities for monitoring conditions that impact community health. Urban blight-manifestations of adverse social processes in the urban enviro...

Enhancing educational semantic retrieval through dual objective fine tuning of open source embedding models

Abstract Recent advances in AI have catalyzed the adoption of intelligent educational tools, yet many semantic retrieval systems remain ill-suited to the unique linguistic and structural characteristics of academic content. This study prese...

Instance-Level Weighted Contrast Learning for Text Classification

With the explosion of information, the amount of text data has increased significantly, making text categorization a central area of research in natural language processing (NLP). Traditional machine learning methods are effective, but deep...

Natural Language Processing Advancements By Deep Learning: A Survey

Natural Language Processing (NLP) helps empower intelligent machines by enhancing a better understanding of the human language for linguistic-based human-computer communication. Recent developments in computational power and the advent of l...

Tracking discussions of complementary, alternative, and integrative medicine in the context of the COVID-19 pandemic: a month-by-month sentiment analysis of Twitter data

Abstract Background Coronavirus disease 2019 (COVID-19) is a novel infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite the paucity of evidence, various complementary, alternative and integr...

Prioritized replay dueling double DQN for intelligent task scheduling in IoT Fog Cloud computing

Abstract Task scheduling remains a challenge in IoT-Fog-Cloud systems due to dynamic workloads and heterogeneous resources. Ineffective scheduling strategies increase latency, energy consumption, and Service Level Agreement (SLA) violations...

Enhancing adult lifelong learning through data fusion algorithms and quality assurance

Abstract This study presents a Data Fusion + Random Forest (RF) framework to predict adult learners’ educational outcomes, such as dropout risk and course completion. Adult lifelong learning is crucial for personal and professional growth, ...

Cracking the code: AI’s role in mapping evidence syntheses to the United Nations sustainable development goals

Abstract Background Understanding the alignment and contributions of research to the United Nations Sustainable Development Goals (UN SDGs) is essential for guiding global progress toward these critical targets. Several SDG mapping approach...

Valorisation of agri-food by-products into bioactive compounds: Green extraction, microbial biotransformation and circular biorefinery strategies

Agri-food processing generates large volumes of by-products that remain insufficiently exploited despite their content of phenolic compounds, peptides, polysaccharides, carotenoids, dietary fibres and other functional constituents. These si...

Strategies for Natural Language Processing

Assessing GPT's capabilities in consumer food survey analysis: A comparative approach for understanding food technophobia and novel protein perceptions

This study explores the application of GPT models for automating consumer food survey analysis, focusing on Chinese consumers' acceptance of plant-based foods, cultured meat, insect-based proteins, and microbial proteins. Traditional survey...

Artificial Intelligence in Routine IVF Practice

Background: Artificial Intelligence (AI) has emerged as a transformative tool in in vitro fertilization (IVF) as it has done in other sectors. In IVF, AI offers advancements in embryo selection, treatment personalization, and outcome predic...

Automated Burr Quality Classification in Drilling of AA6013 Aluminum Alloy Using YOLOv10n

Burr formation during drilling of aluminum alloys can compromise hole quality and assembly accuracy, increasing the need for secondary deburring operations. The time-consuming and operator-dependent nature of manual visual inspection create...