AIMC Topic: Language

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Effects of Language Differences on Inpatient Fall Detection Using Deep Learning.

Studies in health technology and informatics
This study examined the effects of language differences between Korean and English on the performance of natural language processing in the classification task of identifying inpatient falls from unstructured nursing notes.

Updated Primer on Generative Artificial Intelligence and Large Language Models in Medical Imaging for Medical Professionals.

Korean journal of radiology
The emergence of Chat Generative Pre-trained Transformer (ChatGPT), a chatbot developed by OpenAI, has garnered interest in the application of generative artificial intelligence (AI) models in the medical field. This review summarizes different gener...

Data governance and Gensini score automatic calculation for coronary angiography with deep-learning-based natural language extraction.

Mathematical biosciences and engineering : MBE
With the widespread adoption of electronic health records, the amount of stored medical data has been increasing. Clinical data, often in the form of semi-structured or unstructured electronic medical records (EMRs), contains rich patient information...

Advancing Medical Practice with Artificial Intelligence: ChatGPT in Healthcare.

The Israel Medical Association journal : IMAJ
BACKGROUND: Advancements in artificial intelligence (AI) and natural language processing (NLP) have led to the development of language models such as ChatGPT. These models have the potential to transform healthcare and medical research. However, unde...

Human versus artificial intelligence-generated arthroplasty literature: A single-blinded analysis of perceived communication, quality, and authorship source.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Large language models (LLM) have unknown implications for medical research. This study assessed whether LLM-generated abstracts are distinguishable from human-written abstracts and to compare their perceived quality.

Phase-encoded fMRI tracks down brainstorms of natural language processing with subsecond precision.

Human brain mapping
Natural language processing unfolds information overtime as spatially separated, multimodal, and interconnected neural processes. Existing noninvasive subtraction-based neuroimaging techniques cannot simultaneously achieve the spatial and temporal re...

Spotlight on Leadership: What Nurse Leaders Need to Know About Artificial Intelligence.

The Journal of nursing administration
Artificial intelligence (AI) is not a new concept. Since the 2022 release of a popular large language model, AI has become readily accessible to the general population, brought transformational shifts in healthcare, and created significant implicatio...

Using Natural Language Processing to Predict Risk in Electronic Health Records.

Studies in health technology and informatics
Clinical narratives recording behaviours and emotions of patients are available from EHRs in a forensic psychiatric centre located in Tasmania. This rich data has not been used in risk prediction. Prior work demonstrates natural language processing c...

AutoCriteria: a generalizable clinical trial eligibility criteria extraction system powered by large language models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: We aim to build a generalizable information extraction system leveraging large language models to extract granular eligibility criteria information for diverse diseases from free text clinical trial protocol documents. We investigate the ...