Named Entity Recognition (NER) plays a crucial role in extracting important information such as treatment methods, symptoms, and herbal prescriptions from Traditional Chinese Medicine (TCM) electronic medical records. However, existing NER methods of...
BACKGROUND: Drug-drug interactions (DDIs) frequently occur in combination therapy and may cause adverse effects or reduced efficacy. Existing computational approaches often fail to capture both the semantic information in drug sequences and the struc...
BMC medical informatics and decision making
Oct 29, 2025
BACKGROUND: In clinical research, there is a strong drive to leverage big data from population cohort studies and routine electronic healthcare records to design new interventions, improve health outcomes and increase the efficiency of healthcare del...
This study compares generative artificial intelligence (GenAI) and neural machine translation (NMT) systems in translating Uighur literary text (قۇتادغۇ بىلىك)into English. Two NMT systems, Google Translate and Bing Translator, were evaluated alongsi...
Aspect-level sentiment analysis is a significant task in the field of natural language processing. It can process text in a fine-grained manner to predict the sentiment polarity of a specific aspect word in a sentence. However, existing single-channe...
BACKGROUND: Emoji are a universal visual language widely used in digital communication; yet, their representation of medical concepts remains limited. The introduction of medical emojis, such as the anatomical heart and lungs, highlights their potent...
Chinese Named Entity Recognition (NER) is a fundamental task in the field of natural language processing, where achieving deep semantic mining of nested entities and accurate disambiguation of character-level boundary ambiguities stands as its core c...
When using the Property Listing Task (PLT) to collect semantic content for a set of concepts (Concept Property Norms, CPNs), coding raw properties into standardized labels poses significant challenges. In this work, we address these challenges by enh...
The core challenge of Knowledge Base Question Answering (KBQA), as a bridge between natural language and structured knowledge, is to accurately map complex semantic queries into Graph Query Language (GQL). Compared with the traditional Text-to-SQL ta...
Habitat monitoring has emerged as a crucial practice for preserving ecological environments and ensuring species reproduction. Traditional habitat modeling often relies on the "lasagna model"-a McHarg-style approach that focuses on the ecological nic...
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