AIMC Topic: Natural Language Processing

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Identification of neurological text markers associated with risk of stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: Delayed or missed stroke diagnosis is associated with poor outcomes. We utilized natural language processing of notes from non-neurological emergency department (ED) encounters to identify text phrases indicating stroke presentations that...

Enhancing Pulmonary Disease Prediction Using Large Language Models With Feature Summarization and Hybrid Retrieval-Augmented Generation: Multicenter Methodological Study Based on Radiology Report.

Journal of medical Internet research
BACKGROUND: The rapid advancements in natural language processing, particularly the development of large language models (LLMs), have opened new avenues for managing complex clinical text data. However, the inherent complexity and specificity of medi...

Chinese medical named entity recognition based on multimodal information fusion and hybrid attention mechanism.

PloS one
Chinese Medical Named Entity Recognition (CMNER) seeks to identify and extract medical entities from unstructured medical texts. Existing methods often depend on single-modality representations and fail to fully exploit the complementary nature of di...

Evaluating large language models for information extraction from gastroscopy and colonoscopy reports through multi-strategy prompting.

Journal of biomedical informatics
OBJECTIVE: To systematically evaluate large language models (LLMs) for automated information extraction from gastroscopy and colonoscopy reports through prompt engineering, addressing their ability to extract structured information, recognize complex...

Detecting the clinical features of difficult-to-treat depression using synthetic data from large language models.

Computers in biology and medicine
Difficult-to-treat depression (DTD) has been proposed as a broader and more clinically comprehensive perspective on a person's depressive disorder where, despite treatment, they continue to experience significant burden. We sought to develop a tool c...

Assessing the accuracy and consistency of large language models in triaging social media posts for psychological distress.

Psychiatry research
Advances in artificial intelligence, particularly in natural language processing, offer promising tools for addressing mental health challenges in online contexts, potentially identifying at-risk individuals and informing timely interventions. This s...

Tailoring task arithmetic to address bias in models trained on multi-institutional datasets.

Journal of biomedical informatics
OBJECTIVE: Multi-institutional datasets are widely used for machine learning from clinical data, to increase dataset size and improve generalization. However, deep learning models in particular may learn to recognize the source of a data element, lea...

Extending CARDIO:DE: Additional annotation guidelines and evaluation of NLP approaches for clinical applications.

International journal of medical informatics
BACKGROUND: Cardiovascular diseases are a major cause of morbidity and mortality, and the management of these conditions generates extensive clinical data. The CARDIO:DE dataset, a German-language corpus of cardiovascular clinical routine letters, ha...

Comparative analysis of AI algorithms on real medical data for chronic pain detection.

International journal of medical informatics
BACKGROUND AND OBJECTIVE: Chronic pain is a pervasive healthcare challenge with profound implications for patient well-being, clinical decision-making, and resource allocation. Traditional detection methods often rely on subjective assessments and ma...

First impressions of a humanoid social robot with natural language capabilities.

Scientific reports
Concurrent developments in robotic design and natural language processing (NLP) have enabled the production of humanoid chatbots that can operate in commercial and community settings. Though still novel, the presence of physically embodied social rob...