AIMC Topic: Natural Language Processing

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Semiology Extraction and Machine Learning-Based Classification of Electronic Health Records for Patients With Epilepsy: Retrospective Analysis.

JMIR medical informatics
BACKGROUND: Obtaining and describing semiology efficiently and classifying seizure types correctly are crucial for the diagnosis and treatment of epilepsy. Nevertheless, there exists an inadequacy in related informatics resources and decision support...

Enhancing Aortic Aneurysm Surveillance: Transformer Natural Language Processing for Flagging and Measuring in Radiology Reports.

Annals of vascular surgery
BACKGROUND: Incidental findings of aortic aneurysms (AAs) often go unreported, and established patients are frequently lost to follow-up. Natural language processing (NLP) offers a promising solution to address these issues. While rule-based NLP meth...

Identification of cultural conversations in therapy using natural language processing models.

Psychotherapy (Chicago, Ill.)
Researchers have historically focused on understanding therapist multicultural competency and orientation through client self-report measures and behavioral coding. While client perceptions of therapist cultural competency and multicultural orientati...

Analysis of ChatGPT in the Triage of Common Spinal Complaints.

World neurosurgery
BACKGROUND: ChatGPT is a natural language processing chatbot with a significant prevalence in modern media with a clear application in the medical triage workflow. ChatGPT has shown significant capacity for understanding clinical vignettes, radiology...

Introducing high correlation and high quality instances for few-shot entity linking.

Neural networks : the official journal of the International Neural Network Society
Entity linking, the process of connecting textual mentions in documents to canonical entities within a knowledge base, plays an integral role in a myriad of natural language processing tasks. A significant challenge prevalent within the field is the ...

Learning to match patients to clinical trials using large language models.

Journal of biomedical informatics
OBJECTIVE: This study investigates the use of Large Language Models (LLMs) for matching patients to clinical trials (CTs) within an information retrieval pipeline. Our objective is to enhance the process of patient-trial matching by leveraging the se...

Boundary-Aware Dual Biaffine Model for Sequential Sentence Classification in Biomedical Documents.

IEEE/ACM transactions on computational biology and bioinformatics
Assigning appropriate rhetorical roles, such as "background," "intervention," and "outcome," to sentences in biomedical documents can streamline the process for physicians to locate evidence and resources for medical treatment and decision-making. Wh...

Evaluating the positive predictive value of code-based identification of cirrhosis and its complications utilizing GPT-4.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Diagnosis code classification is a common method for cohort identification in cirrhosis research, but it is often inaccurate and augmented by labor-intensive chart review. Natural language processing using large language models (...

Perceived Impact of COVID-19 in an Underserved Community: A Natural Language Processing Approach.

Journal of advanced nursing
AIM: To utilise natural language processing (NLP) to analyse interviews about the impact of COVID-19 in underserved communities and to compare it to traditional thematic analysis in a small subset of interviews.

Advances of artificial intelligence in predicting frailty using real-world data: A scoping review.

Ageing research reviews
BACKGROUND: Frailty assessment is imperative for tailoring healthcare interventions for older adults, but its implementation remains challenging due to the effort and time needed. The advances of artificial intelligence (AI) and natural language proc...