AIMC Topic: Natural Language Processing

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Assessing Completeness of Clinical Histories Accompanying Imaging Orders Using Adapted Open-Source and Closed-Source Large Language Models.

Radiology
Background Incomplete clinical histories are a well-known problem in radiology. Previous dedicated quality improvement efforts focusing on reproducible assessments of the completeness of free-text clinical histories have relied on tedious manual anal...

Computing 3-Step Theory of Suicide Factor Scores From Veterans Health Administration Clinical Progress Notes.

Suicide & life-threatening behavior
BACKGROUND: Literature on how to translate information extracted from clinical progress notes into numeric scores for 3-step theory of suicide (3ST) factors is nonexistent. We determined which scoring option would best discriminate between patients w...

CARE-SD: classifier-based analysis for recognizing provider stigmatizing and doubt marker labels in electronic health records: model development and validation.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To detect and classify features of stigmatizing and biased language in intensive care electronic health records (EHRs) using natural language processing techniques.

Application of large language models in clinical record correction: a comprehensive study on various retraining methods.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: We evaluate the effectiveness of large language models (LLMs), specifically GPT-based (GPT-3.5 and GPT-4) and Llama-2 models (13B and 7B architectures), in autonomously assessing clinical records (CRs) to enhance medical education and dia...

Lessons learned on information retrieval in electronic health records: a comparison of embedding models and pooling strategies.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Applying large language models (LLMs) to the clinical domain is challenging due to the context-heavy nature of processing medical records. Retrieval-augmented generation (RAG) offers a solution by facilitating reasoning over large text so...

Beyond electronic health record data: leveraging natural language processing and machine learning to uncover cognitive insights from patient-nurse verbal communications.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Mild cognitive impairment and early-stage dementia significantly impact healthcare utilization and costs, yet more than half of affected patients remain underdiagnosed. This study leverages audio-recorded patient-nurse verbal communicatio...

LCD benchmark: long clinical document benchmark on mortality prediction for language models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: The application of natural language processing (NLP) in the clinical domain is important due to the rich unstructured information in clinical documents, which often remains inaccessible in structured data. When applying NLP methods to a c...

Identifying stigmatizing and positive/preferred language in obstetric clinical notes using natural language processing.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To identify stigmatizing language in obstetric clinical notes using natural language processing (NLP).

Testing and Evaluation of Health Care Applications of Large Language Models: A Systematic Review.

JAMA
IMPORTANCE: Large language models (LLMs) can assist in various health care activities, but current evaluation approaches may not adequately identify the most useful application areas.

A case study of forensic psychiatry experts' reports analysis through large language models.

International journal of law and psychiatry
The integration of artificial intelligence (AI) technologies in forensic psychiatry has gained significant attention due to their potential to enhance tasks such as outcome prediction and decision-making. In this study, we explored the feasibility an...