BACKGROUND: Subjective report of pain remains the gold standard for assessing symptoms in patients with chronic pain and their response to analgesics. This subjectivity underscores the importance of understanding patients' personal narratives, as the...
OBJECTIVES: Postoperative complications (PCs) require substantial resources to manage and are cumbersome to monitor. Artificial intelligence (AI), particularly natural language processing (NLP), offers a potential solution by automating and streamlin...
Named Entity Recognition (NER) stands as a fundamental task in Chinese information processing. However, it encounters unique difficulties due to the lack of explicit word boundaries in the Chinese language. This study proposes framing Chinese NER as ...
With the rapid development of artificial intelligence (AI), deep learning has provided new ideas for the patent protection of biological genetic resources in the field of intellectual property. This paper aims to explore the application of deep learn...
To reduce hallucinations in large language models (LLMs), retrieval-augmented LLMs (RALs) retrieve supporting knowledge from external databases. However, their performance on biomedical natural language processing (NLP) tasks remains underexplored. W...
BACKGROUND: In the face of pandemics from infectious diseases, enhancing community resilience is increasingly important. It is, therefore, essential to evaluate community resilience and identify factors that can strengthen it. This study aimed to eva...
The issue of generating a natural language explanation of images to define their visual content has garnered significant attention in computer vision (CV) and natural language processing (NLP). It is driven by applications such as image virtual assis...
World journal of microbiology & biotechnology
Nov 18, 2025
There is a growing concern about fungal infections and antifungal resistance among fungal species, underscoring the need for finding alternative treatments. Antifungal peptides (AFPs) are interesting and promising candidates for developing novel anti...
This paper evaluates the effectiveness of large language models (LLMs) in extracting complex information from text data. Using a corpus of Spanish news articles, we compare how accurately various LLMs and outsourced human coders reproduce expert anno...
BACKGROUND: The unstructured data of Chinese cancer electronic health records (EHRs) contains valuable medical expertise. Accurate medical entity recognition is crucial for building a medical-assisted decision system. Named entity recognition (NER) i...
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