Recent advancements in Artificial Intelligence have yielded promising results in addressing complex challenges within Natural Language Processing (NLP), serving as a vital tool for expediting judicial proceedings in the legal domain. This study focus...
The rapid growth of biomedical literature poses challenges for manual knowledge curation and synthesis. Biomedical Natural Language Processing (BioNLP) automates the process. While Large Language Models (LLMs) have shown promise in general domains, t...
OBJECTIVES: Large language models (LLMs) are revolutionizing the natural language pro-cessing (NLP) landscape within healthcare, prompting the need to synthesize the latest ad-vancements and their diverse medical applications. We attempt to summarize...
OBJECTIVE: To explore how artificial intelligence (AI) methodologies, particularly through the analysis of social media content, can enhance "precision in prevention and health surveillance" (2024 Yearbook topic). The focus is on leveraging advanced ...
OBJECTIVES: The emergence of large language models has resulted in a significant shift in informatics research and carries promise in clinical cancer care. Here we provide a narrative review of the recent use of large language models (LLMs) to suppor...
Given the scarcity of annotated data, current deep learning methods face challenges in the field of document-level chemical-disease relation extraction, making it difficult to achieve precise relation extraction capable of identifying relation types ...
Clinical oncology (Royal College of Radiologists (Great Britain))
40188745
AIMS: Patient data is frequently stored as unstructured data within Electronic Health Records (EHRs), requiring manual curation. AI tools using Natural Language Processing (NLP) may rapidly curate accurate real-world unstructured EHRs to enrich datas...
OBJECTIVE: Electronic health records (EHR) are widely available to complement administrative data-based disease surveillance and healthcare performance evaluation. Defining conditions from EHR is labour-intensive and requires extensive manual labelli...
BACKGROUND: Popularized by ChatGPT, large language models (LLMs) are poised to transform the scalability of clinical natural language processing (NLP) downstream tasks such as medical question answering (MQA) and automated data extraction from clinic...
Despite regulatory efforts, many smartphone health applications remain unregulated, raising concerns about privacy, security, and evidence-based effectiveness. The lack of standardized regulation has led to the proliferation of over 130 frameworks, i...