Sarcasm detection in natural language processing (NLP) remains a complex challenge, especially in social media, where contextual clues are often subtle. This study addresses this challenge by leveraging transformer-based models, including BERT, GPT-3...
Data extraction from medical records is crucial for clinical research, with current methods relying on human annotation. Natural Language Processing (NLP) and Machine Learning-based approaches show promise. We develop and evaluate an NLP pipeline con...
Textemotion detection constitutes a crucial foundation for advancing artificial intelligence from basic comprehension to the exploration of emotional reasoning. Most existing emotion detection datasets rely on manual annotations, which are associated...
Visual question answering (VQA) as an interdisciplinary task of computer vision and natural language processing, estimating the model's visual reasoning ability, which requires the integration of image information extraction technology and natural la...
Sentiment analysis is a pivotal domain in Natural Language Processing (NLP), particularly for understanding opinions expressed in sequential and textual data with the usage of machine learning. It involves identifying and categorizing emotions expres...
BACKGROUND: Manual review of electronic health records for clinical research is labor-intensive and prone to reviewer-dependent variations. Large language models (LLMs) offer potential for automated clinical data extraction; however, their feasibilit...
Natural language is a primary medium for expressing thoughts and emotions, making text analysis a vital tool in psychological research. It enables insights into personality traits, mental health, and sentiment in interpersonal communication. Traditio...
Large language models (LLMs) excel in many natural language processing tasks. However, their direct application to tabular, domain-specific clinical data remains challenging, as they lack innate mechanisms for reasoning over structured numerical feat...
BACKGROUND: Extracting genetic phenotype mentions from clinical reports and normalizing them to standardized concepts within the human phenotype ontology are essential for consistent interpretation and representation of genetic conditions. This is pa...
Emotion recognition is an important research field including psychology, healthcare, and human-computer interaction (HCI). However, conventional techniques mainly rely on textual analysis and facial expressions, and they also have potential flaws, ma...
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