AIMC Topic: Natural Language Processing

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Natural language processing in at-risk mental states: enhancing the assessment of thought disorders and psychotic traits with semantic dynamics and graph theory.

Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999) Jul 29, 2024
OBJECTIVE: Verbal communication contains key information for mental health assessment. Researchers have linked psychopathology phenomena to certain counterparts in natural language processing. We characterized subtle impairments in the early stages o...
Semantics Male Natural Language Processing Brazil Psychotic Disorders Psychiatric Status Rating Scales Humans Adolescent Young Adult Female Case-Control Studies Adult
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Textual emotion classification using MPNet and cascading broad learning.

Neural networks : the official journal of the International Neural Network Society Jul 27, 2024
As one of the most important tasks of natural language processing, textual emotion classification (TEC) aims to recognize and detect all emotions contained in texts. However, most existing methods are implemented using deep learning approaches, which...
Humans Neural Networks, Computer Deep Learning Emotions Natural Language Processing Semantics
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Using natural language processing to evaluate temporal patterns in suicide risk variation among high-risk Veterans.

Psychiatry research Jul 27, 2024
Measuring suicide risk fluctuation remains difficult, especially for high-suicide risk patients. Our study addressed this issue by leveraging Dynamic Topic Modeling, a natural language processing method that evaluates topic changes over time, to anal...
United States Department of Veterans Affairs Veterans Risk Assessment Case-Control Studies Humans United States Adult Electronic Health Records Natural Language Processing Suicide Female Male Middle Aged
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Diagnostic accuracy of large language models in psychiatry.

Asian journal of psychiatry Jul 25, 2024
INTRODUCTION: Medical decision-making is crucial for effective treatment, especially in psychiatry where diagnosis often relies on subjective patient reports and a lack of high-specificity symptoms. Artificial intelligence (AI), particularly Large La...
Clinical Decision-Making Adult Diagnostic and Statistical Manual of Mental Disorders Natural Language Processing Mental Disorders Humans Psychiatry Artificial Intelligence
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Understanding natural language: Potential application of large language models to ophthalmology.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.) Jul 25, 2024
Large language models (LLMs), a natural language processing technology based on deep learning, are currently in the spotlight. These models closely mimic natural language comprehension and generation. Their evolution has undergone several waves of in...
Artificial Intelligence Deep Learning Ophthalmology Natural Language Processing Humans Neural Networks, Computer
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Natural Language Processing in medicine and ophthalmology: A review for the 21st-century clinician.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.) Jul 25, 2024
Natural Language Processing (NLP) is a subfield of artificial intelligence that focuses on the interaction between computers and human language, enabling computers to understand, generate, and derive meaning from human language. NLP's potential appli...
Natural Language Processing Ophthalmology Artificial Intelligence Electronic Health Records Humans
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[Large language models in science].

Urologie (Heidelberg, Germany) Jul 24, 2024
OBJECTIVE: Large language models (LLMs) are gaining popularity due to their ability to communicate in a human-like manner. Their potential for science, including urology, is increasingly recognized. However, unresolved concerns regarding transparency...
Humans Natural Language Processing Urology Science Machine Learning Language
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A pseudonymized corpus of occupational health narratives for clinical entity recognition in Spanish.

BMC medical informatics and decision making Jul 24, 2024
Despite the high creation cost, annotated corpora are indispensable for robust natural language processing systems. In the clinical field, in addition to annotating medical entities, corpus creators must also remove personally identifiable informatio...
Humans Occupational Health Spain Narration Natural Language Processing
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Leveraging shortest dependency paths in low-resource biomedical relation extraction.

BMC medical informatics and decision making Jul 24, 2024
BACKGROUND: Biomedical Relation Extraction (RE) is essential for uncovering complex relationships between biomedical entities within text. However, training RE classifiers is challenging in low-resource biomedical applications with few labeled exampl...
Humans Data Mining Machine Learning Natural Language Processing
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Using natural language processing to facilitate the harmonisation of mental health questionnaires: a validation study using real-world data.

BMC psychiatry Jul 24, 2024
BACKGROUND: Pooling data from different sources will advance mental health research by providing larger sample sizes and allowing cross-study comparisons; however, the heterogeneity in how variables are measured across studies poses a challenge to th...
Female United Kingdom Humans Adult Semantics Male Surveys and Questionnaires Mental Health Middle Aged Natural Language Processing
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