AIMC Topic: Natural Language Processing

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SpeLL: An Agent for Natural Language-Driven Intelligent Spectral Modeling.

Journal of chemical information and modeling
Spectrum large language model (SpeLL) was developed to tackle core challenges in near-infrared (NIR) spectral data modeling─the high level of expertise and substantial workload required by researchers for method selection, implementation, and optimiz...

Improving Large Language Models' Summarization Accuracy by Adding Highlights to Discharge Notes: Comparative Evaluation.

JMIR medical informatics
BACKGROUND: The American Medical Association recommends that electronic health record (EHR) notes, often dense and written in nuanced language, be made readable for patients and laypeople, a practice we refer to as the simplification of discharge not...

A natural language processing approach to support biomedical data harmonization: Leveraging large language models.

PloS one
BACKGROUND: Biomedical research requires large, diverse samples to produce unbiased results. Retrospective data harmonization is often used to integrate existing datasets to create these samples, but the process is labor-intensive. Automated methods ...

Can GPT-4 provide human-level emotion support? Insights from machine learning-based evaluation framework.

Computers in biology and medicine
The global shortage of mental health services has sparked considerable interest in leveraging generative artificial intelligence (AI) to address psychological health challenges. This study systematically evaluates the emotional support capabilities o...

Multilingual identification of nuanced dimensions of hope speech in social media texts.

Scientific reports
Hope plays a crucial role in human psychology and well-being, yet its expression and detection across languages remain underexplored in natural language processing (NLP). This study presents MIND-HOPE, the first-ever multiclass hope speech detection ...

Natural Language Processing framework for identifying abdominal aortic aneurysm repairs using unstructured electronic health records.

Scientific reports
Patient identification for national registries often relies upon clinician recognition of cases or retrospective searches using potentially inaccurate clinical codes, leading to incomplete data capture and inefficiencies. Natural Language Processing ...

Multicriteria Optimization of Language Models for Heart Failure With Preserved Ejection Fraction Symptom Detection in Spanish Electronic Health Records: Comparative Modeling Study.

Journal of medical Internet research
BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) is a major clinical manifestation of cardiac amyloidosis, a condition frequently underdiagnosed due to its nonspecific symptomatology. Electronic health records (EHRs) offer a promisi...

Developing the CAM-BERT: Enhancing delirium screening in hospitalized older adults using natural language processing.

Computers in biology and medicine
BACKGROUND: Delirium is a common condition affecting hospitalized older adults, often leading to adverse outcomes. Nevertheless, delirium frequently goes unrecognized due to various clinical and systemic challenges. We aimed to develop and evaluate a...

Advancing psychological assessment: quantifying self-compassion through free-text responses and language model BERT.

Scientific reports
Self-compassion, which refers to compassion directed toward oneself, is associated with mental health and well-being. Traditionally, self-compassion has been measured and quantified using rating scales such as the Self-Compassion Scale (SCS) and Comp...

A method for English paragraph grammar correction based on differential fusion of syntactic features.

PloS one
The new progress of deep learning and natural language processing technology has strongly promoted the development of English grammar error correction. However, the existing methods mostly rely on large-scale corpus, and often ignore the fine syntact...