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Natural Language Processing

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Speech and language patterns in autism: Towards natural language processing as a research and clinical tool.

Psychiatry research
Speech and language differences have long been described as important characteristics of autism spectrum disorder (ASD). Linguistic abnormalities range from prosodic differences in pitch, intensity, and rate of speech, to language idiosyncrasies and ...

Cross-lingual hate speech detection using domain-specific word embeddings.

PloS one
THIS ARTICLE USES WORDS OR LANGUAGE THAT IS CONSIDERED PROFANE, VULGAR, OR OFFENSIVE BY SOME READERS. Hate speech detection in online social networks is a multidimensional problem, dependent on language and cultural factors. Most supervised learning ...

Transformer models in biomedicine.

BMC medical informatics and decision making
Deep neural networks (DNN) have fundamentally revolutionized the artificial intelligence (AI) field. The transformer model is a type of DNN that was originally used for the natural language processing tasks and has since gained more and more attentio...

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)
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...

Textual emotion classification using MPNet and cascading broad learning.

Neural networks : the official journal of the International Neural Network Society
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...

Using natural language processing to evaluate temporal patterns in suicide risk variation among high-risk Veterans.

Psychiatry research
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...

Diagnostic accuracy of large language models in psychiatry.

Asian journal of psychiatry
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...

Understanding natural language: Potential application of large language models to ophthalmology.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
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...

Natural Language Processing in medicine and ophthalmology: A review for the 21st-century clinician.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
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...

[Large language models in science].

Urologie (Heidelberg, Germany)
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...