AIMC Topic: Natural Language Processing

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Monitoring Opioid-Related Social Media Chatter Using Natural Language Processing and Large Language Models: Temporal Analysis.

JMIR infodemiology
BACKGROUND: Opioid overdose is a global public health emergency, with the United States experiencing high rates of morbidity and mortality due to prescription and illicit opioid use. Traditional public health monitoring systems often fail to provide ...

Nested named entity recognition in traditional Chinese medicine electronic medical records via dual-granularity feature augmentation and span classification.

Scientific reports
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...

Clinician-in-the-loop screening saturation: predicting annotation yield for efficient EHR review.

BMC medical informatics and decision making
BACKGROUND: Labor- and cost-intensive manual chart review of Electronic Health Records (EHRs) remains a major bottleneck in retrospective studies, particularly when rare-disease cohorts require high specificity. Automated Natural Language Processing ...

Natural language processing of gene descriptions for overrepresentation analysis with GeneTEA.

Genome biology
Overrepresentation analysis is used to identify biological enrichment in a list of genes. Here, we introduce GeneTEA, a model that ingests free-text gene descriptions and incorporates natural language processing methods to learn a sparse gene-by-term...

An integrated approach for rare disease detection and classification in Spanish pediatric medical reports.

Scientific reports
Rare disease detection and classification is one of the most significant challenges in the application of Natural Language Processing techniques to the analysis and extraction of information from biomedical texts. In this paper, we present a novel re...

Pretrained language models for semantics-aware data harmonisation of observational clinical studies in the era of big data.

BMC medical informatics and decision making
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...

Fine-tuning a sentence transformer for DNA.

BMC bioinformatics
BACKGROUND: Sentence-transformers is a library that provides easy methods for generating embeddings for sentences, paragraphs, and images. Sentiment analysis, retrieval, and clustering are among the applications made possible by the embedding of text...

Public values in public R&D through natural language processing.

Scientific reports
Given South Korea's recent 16.6% reduction in research and development (R&D) budgets for 2023, there is an urgent need for more efficient and strategic R&D policy management. Previous studies evaluating R&D outputs have primarily relied on quantitati...

Human-Machine Agreement in Medical Ethics: Patient Autonomy Case-Based Evaluation of Large Language Models.

JMIR medical informatics
BACKGROUND: Medical ethics provides a moral framework for the practice of clinical medicine. Four principles, that is, beneficence, nonmaleficence, patient autonomy, and justice, form the cornerstones of medical ethics as it is practiced today. Of th...

From words to action? A scoping review on automatic sentiment analysis of patient experience comments from online sources and surveys.

BMJ health & care informatics
BACKGROUND: Automatic analysis of free-text patient comments enables the efficient processing of large feedback volumes, reducing reliance on manual review. A 2021 review examined natural language processing (NLP) and sentiment analysis (SA) in patie...