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Bridging the Gap: Can Large Language Models Match Human Expertise in Writing Neurosurgical Operative Notes?

World neurosurgery
BACKGROUND: Proper documentation is essential for patient care. The popularity of artificial intelligence (AI) offers the potential for improvements in neurosurgical note-writing. This study aimed to assess how AI can optimize documentation in neuros...

FLAT: Fusing layer representations for more efficient transfer learning in NLP.

Neural networks : the official journal of the International Neural Network Society
Parameter efficient transfer learning (PETL) methods provide an efficient alternative for fine-tuning. However, typical PETL methods inject the same structures to all Pre-trained Language Model (PLM) layers and only use the final hidden states for do...

Language discrepancies in the performance of generative artificial intelligence models: an examination of infectious disease queries in English and Arabic.

BMC infectious diseases
BACKGROUND: Assessment of artificial intelligence (AI)-based models across languages is crucial to ensure equitable access and accuracy of information in multilingual contexts. This study aimed to compare AI model efficiency in English and Arabic for...

Ethical Considerations and Fundamental Principles of Large Language Models in Medical Education: Viewpoint.

Journal of medical Internet research
This viewpoint article first explores the ethical challenges associated with the future application of large language models (LLMs) in the context of medical education. These challenges include not only ethical concerns related to the development of ...

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 ...

Using artificial intelligence to generate medical literature for urology patients: a comparison of three different large language models.

World journal of urology
PURPOSE: Large language models (LLMs) are a form of artificial intelligence (AI) that uses deep learning techniques to understand, summarize and generate content. The potential benefits of LLMs in healthcare is predicted to be immense. The objective ...

[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...

Online content on eating disorders: a natural language processing study.

Journal of communication in healthcare
BACKGROUND: Online content can inform the personal risk of developing an eating disorder, and it can influence the time and motivation to seek treatment. Patients routinely seek information online, and access to information is crucial for both preven...