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Natural Language Processing

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Contextualized race and ethnicity annotations for clinical text from MIMIC-III.

Scientific data
Observational health research often relies on accurate and complete race and ethnicity (RE) patient information, such as characterizing cohorts, assessing quality/performance metrics of hospitals and health systems, and identifying health disparities...

Machine Learning-Based Suicide Risk Prediction Model for Suicidal Trajectory on Social Media Following Suicidal Mentions: Independent Algorithm Validation.

Journal of medical Internet research
BACKGROUND: Previous efforts to apply machine learning-based natural language processing to longitudinally collected social media data have shown promise in predicting suicide risk.

Integrating structured and unstructured data for predicting emergency severity: an association and predictive study using transformer-based natural language processing models.

BMC medical informatics and decision making
BACKGROUND: Efficient triage in emergency departments (EDs) is critical for timely and appropriate care. Traditional triage systems primarily rely on structured data, but the increasing availability of unstructured data, such as clinical notes, prese...

CALLM: Enhancing Clinical Interview Analysis Through Data Augmentation With Large Language Models.

IEEE journal of biomedical and health informatics
The global prevalence of mental health disorders is increasing, leading to a significant economic burden estimated in trillions of dollars. In automated mental health diagnosis, the scarcity and imbalance of clinical data pose considerable challenges...

Care home resident identification: A comparison of address matching methods with Natural Language Processing.

PloS one
BACKGROUND: Care home residents are a highly vulnerable group, but identifying care home residents in routine data is challenging. This study aimed to develop and validate Natural Language Processing (NLP) methods to identify care home residents from...

An automated approach to identify sarcasm in low-resource language.

PloS one
Sarcasm detection has emerged due to its applicability in natural language processing (NLP) but lacks substantial exploration in low-resource languages like Urdu, Arabic, Pashto, and Roman-Urdu. While fewer studies identifying sarcasm have focused on...

Nonnegative matrix factorization with Wasserstein metric-based regularization for enhanced text embedding.

PloS one
Text embedding plays a crucial role in natural language processing (NLP). Among various approaches, nonnegative matrix factorization (NMF) is an effective method for this purpose. However, the standard NMF approach, fundamentally based on the bag-of-...

Understanding veterinary practitioners' responses to adverse events using a combined grounded theory and netnographic natural language processing approach.

PloS one
Support that mitigates the detrimental impact of adverse events on human healthcare practitioners is underpinned by an understanding of their experiences. This study used a mixed methods approach to understand veterinary practitioners' responses to a...

CPRS: a clinical protocol recommendation system based on LLMs.

International journal of medical informatics
BACKGROUND: As fundamental documents in clinical trials, clinical trial protocols are intended to ensure that trials are conducted according to the objectives set by researchers. The advent of large models with superior semantic performance compared ...

Automated derivation of diagnostic criteria for lung cancer using natural language processing on electronic health records: a pilot study.

BMC medical informatics and decision making
BACKGROUND: The digitisation of healthcare records has generated vast amounts of unstructured data, presenting opportunities for improvements in disease diagnosis when clinical coding falls short, such as in the recording of patient symptoms. This st...