AIMC Topic: Natural Language Processing

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Leveraging Data Pipeline and LLM to Advance Patient Safety Event Studies.

Studies in health technology and informatics
Research utilizing the open-access MAUDE database frequently reveals unclear methodologies for extracting and processing medical device report (MDR) data, reducing reproducibility and consistency. By harnessing the OpenFDA API and our MAUDE extract-t...

Fine-Tuning an Existing Large Language Model with Knowledge from the Medical Expert System Hepaxpert.

Studies in health technology and informatics
The analysis and individual interpretation of hepatitis serology test results is a complex task in laboratory medicine, requiring either experienced physicians or specialized expert systems. This study explores fine-tuning a large language model (LLM...

Validating Hierarchical Alignments of Partially Antonymous Concept Pairs in SNOMED CT.

Studies in health technology and informatics
SNOMED CT is a comprehensive controlled biomedical ontology widely used as an information exchange standard among various healthcare institutions. To ensure the unambiguous expression of health data and effective linguistic computation of word meanin...

Artificial intelligence for severity triage based on conversations in an emergency department in Korea.

Scientific reports
In the fast-paced emergency departments, where crises unfold unpredictably, the systematic prioritization of critical patients based on a severity classification is vital for swift and effective treatment. This study aimed to enhance the quality of e...

End-to-end Chinese clinical event extraction based on large language model.

Scientific reports
Clinical event extraction is crucial for structuring medical data, supporting clinical decision-making, and enabling other intelligent healthcare services. Traditional approaches for clinical event extraction often use pipeline-based methods to ident...

COMPASS: Computational mapping of patient-therapist alliance strategies with language modeling.

Translational psychiatry
The therapeutic working alliance is a critical predictor of psychotherapy success. Traditionally, working alliance assessment relies on questionnaires completed by both therapists and patients. In this paper, we present COMPASS, a novel framework to ...

Extracting Multifaceted Characteristics of Patients With Chronic Disease Comorbidity: Framework Development Using Large Language Models.

JMIR medical informatics
BACKGROUND: Research on chronic multimorbidity has increasingly become a focal point with the aging of the population. Many studies in this area require detailed patient characteristic information. However, the current methods for extracting such inf...

A Deep Learning-Enabled Workflow to Estimate Real-World Progression-Free Survival in Patients With Metastatic Breast Cancer: Study Using Deidentified Electronic Health Records.

JMIR cancer
BACKGROUND: Progression-free survival (PFS) is a crucial endpoint in cancer drug research. Clinician-confirmed cancer progression, namely real-world PFS (rwPFS) in unstructured text (ie, clinical notes), serves as a reasonable surrogate for real-worl...

Scientific Evidence for Clinical Text Summarization Using Large Language Models: Scoping Review.

Journal of medical Internet research
BACKGROUND: Information overload in electronic health records requires effective solutions to alleviate clinicians' administrative tasks. Automatically summarizing clinical text has gained significant attention with the rise of large language models....

Identification of Online Health Information Using Large Pretrained Language Models: Mixed Methods Study.

Journal of medical Internet research
BACKGROUND: Online health information is widely available, but a substantial portion of it is inaccurate or misleading, including exaggerated, incomplete, or unverified claims. Such misinformation can significantly influence public health decisions a...