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Natural Language Processing

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The influence of prompt engineering on large language models for protein-protein interaction identification in biomedical literature.

Scientific reports
Identifying protein-protein interactions (PPIs) is a foundational task in biomedical natural language processing. While specialized models have been developed, the potential of general-domain large language models (LLMs) in PPI extraction, particular...

Cross language transformation of free text into structured lobectomy surgical records from a multi center study.

Scientific reports
In a recent study, the effectiveness of GPT-4 Omni in transforming lobectomy surgical records into structured data across multiple languages was explored. The aim was to improve both efficiency and accuracy in documenting thoracic surgical oncology p...

Automated extraction of functional biomarkers of verbal and ambulatory ability from multi-institutional clinical notes using large language models.

Journal of neurodevelopmental disorders
BACKGROUND: Functional biomarkers in neurodevelopmental disorders, such as verbal and ambulatory abilities, are essential for clinical care and research activities. Treatment planning, intervention monitoring, and identifying comorbid conditions in i...

A Dataset of Real and Synthetic Speech in Ukrainian.

Scientific data
This work is dedicated to the analysis and evaluation of the DRSSU dataset: A Dataset of Real and Synthetic Speech in Ukrainian, created to support research in the field of natural language processing and speech recognition. The dataset contains a un...

Assessing autobiographical memory consistency: Machine and human approaches.

Behavior research methods
Memory is far from a stable representation of what we have encountered. Over time, we can forget, modify, and distort the details of our experiences. How autobiographical memory-the memories we have for our personal past-changes has important ramific...

Dual-stream algorithms for dementia detection: Harnessing structured and unstructured electronic health record data, a novel approach to prevalence estimation.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Identifying individuals with dementia is crucial for prevalence estimation and service planning, but reliable, scalable methods are lacking. We developed novel set algorithms using both structured and unstructured electronic health reco...

The Applications of Large Language Models in Mental Health: Scoping Review.

Journal of medical Internet research
BACKGROUND: Mental health is emerging as an increasingly prevalent public issue globally. There is an urgent need in mental health for efficient detection methods, effective treatments, affordable privacy-focused health care solutions, and increased ...

Systematic Identification of Caregivers of Patients Living With Dementia in the Electronic Health Record: Known Contacts and Natural Language Processing Cohort Study.

Journal of medical Internet research
BACKGROUND: Systemically identifying caregivers in the electronic health record (EHR) is a critical step for delivering patient-centered care, enhancing care coordination, and advancing research and population health efforts in caregiving. Despite EH...

Paraphrase detection for Urdu language text using fine-tune BiLSTM framework.

Scientific reports
Automated paraphrase detection is crucial for natural language processing (NL) applications like text summarization, plagiarism detection, and question-answering systems. Detecting paraphrases in Urdu text remains challenging due to the language's co...

Natural Language Processing and Machine Learning Techniques for Analyzing Conversations About Nutritional Yeasts in the United States and France: Retrospective Social Media Listening Study.

JMIR infodemiology
BACKGROUND: Nutritional yeast, an inactive form of Saccharomyces cerevisiae, has recently become increasingly popular as a food supplement and healthy ingredient, especially among individuals following plant-based diets. It is valued for its health b...