AIMC Topic: Natural Language Processing

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Pilot Application of a Large Language Model to Identify Hospitalisation from Unstructured Electronic Health Records in Residential Aged Care Facilities.

Studies in health technology and informatics
Older people in residential aged care facilities (RACFs) visit hospitals and utilise healthcare services more often than others in the community. Trends in hospitalization rates are essential for designing targeted aged care interventions to reduce p...

Integrating Large Language Models and Machine Learning for Enhanced Catatonia Phenotyping: A Study on Clinical Data from Electronic Health Records.

Studies in health technology and informatics
Catatonia, a complex syndrome with diagnostic challenges, was studied using a novel approach combining LightGBM and GPT-4 to enhance phenotyping from electronic health record (EHR) data. LightGBM, trained on structured data, achieved superior perform...

Designing a Healthcare Co-Pilot with Generative AI.

Studies in health technology and informatics
This paper presents our methodology for designing, testing, and evaluating a co-pilot tailored for healthcare professionals working in Spanish-speaking contexts. The co-pilot facilitates efficient access to textual information from clinical notes and...

A Novel Model for Generating Patient Laboratory Test Orders from Admission: Transformer Model Approach.

Studies in health technology and informatics
There is a growing demand for medical pseudo-data that maintains statistical utility, enabling the analysis of a wide range of medical data without compromising patient privacy. Additionally, there is a growing need for effective sequence prediction ...

Enhancing Interpretability of Ocular Disease Diagnosis: A Zero-Shot Study of Multimodal Large Language Models.

Studies in health technology and informatics
Visual foundation models have advanced ocular disease diagnosis, yet providing interpretable explanations remains challenging. We evaluate multimodal LLMs for generating explanations of ocular diagnoses, combining Vision Transformer-derived saliency ...

Confidence-linked and uncertainty-based staged framework for phenotype validation using large language models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: This study develops and validates the confidence-linked and uncertainty-based staged (CLUES) framework by integrating large language models (LLMs) with uncertainty quantification to assist manual chart review while ensuring reliability th...

Integrating Large language models into radiology workflow: Impact of generating personalized report templates from summary.

European journal of radiology
OBJECTIVE: To evaluate feasibility of large language models (LLMs) to convert radiologist-generated report summaries into personalized report templates, and assess its impact on scan reporting time and quality.

Initial Proof-of-Concept Study for a Plastic Surgery-Specific Artificial Intelligence Large Language Model: PlasticSurgeryGPT.

Aesthetic surgery journal
BACKGROUND: The advent of general-purpose large language models (LLMs) like ChatGPT (OpenAI, San Francisco, CA) has revolutionized natural language processing, but their applicability in specialized medical fields, like plastic surgery, remains limit...

CAS: enhancing implicit constrained data augmentation with semantic enrichment for biomedical relation extraction and beyond.

Database : the journal of biological databases and curation
Biomedical relation extraction often involves datasets with implicit constraints, where structural, syntactic, or semantic rules must be strictly preserved to maintain data integrity. Traditional data augmentation techniques struggle in these scenari...

Genomic language models (gLMs) decode bacterial genomes for improved gene prediction and translation initiation site identification.

Briefings in bioinformatics
Accurate bacterial gene prediction is essential for understanding microbial functions and advancing biotechnology. Traditional methods based on sequence homology and statistical models often struggle with complex genetic variations and novel sequence...