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Artificial Intelligence in Surgical Documentation: A Critical Review of the Role of Large Language Models.

Annals of biomedical engineering
This article provides a critical analysis of the application of the advanced language model, GPT-4, in generating surgical operative notes, with a focus on its use in ophthalmology as presented by Waisberg et al. The discussion underscores the inhere...

Artificial intelligence-driven prediction of COVID-19-related hospitalization and death: a systematic review.

Frontiers in public health
AIM: To perform a systematic review on the use of Artificial Intelligence (AI) techniques for predicting COVID-19 hospitalization and mortality using primary and secondary data sources.

Performance of Generative Large Language Models on Ophthalmology Board-Style Questions.

American journal of ophthalmology
PURPOSE: To investigate the ability of generative artificial intelligence models to answer ophthalmology board-style questions.

Evolving a Pipeline Approach for Abstract Meaning Representation Parsing Towards Dynamic Neural Networks.

International journal of neural systems
Meaning Representation parsing aims to represent a sentence as a structured, Directed, Acyclic Graph (DAG), in an attempt to extract meaning from text. This paper extends an existing 2-stage pipeline AMR parser with state-of-the-art techniques in dep...

Contextualized medication event extraction with striding NER and multi-turn QA.

Journal of biomedical informatics
This paper describes contextualized medication event extraction for automatically identifying medication change events with their contexts from clinical notes. The striding named entity recognition (NER) model extracts medication name spans from an i...

Clinical named entity recognition and relation extraction using natural language processing of medical free text: A systematic review.

International journal of medical informatics
BACKGROUND: Natural Language Processing (NLP) applications have developed over the past years in various fields including its application to clinical free text for named entity recognition and relation extraction. However, there has been rapid develo...

Symbols and grounding in large language models.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Large language models (LLMs) are one of the most impressive achievements of artificial intelligence in recent years. However, their relevance to the study of language more broadly remains unclear. This article considers the potential of LLMs to serve...

Ensemble of deep learning language models to support the creation of living systematic reviews for the COVID-19 literature.

Systematic reviews
BACKGROUND: The COVID-19 pandemic has led to an unprecedented amount of scientific publications, growing at a pace never seen before. Multiple living systematic reviews have been developed to assist professionals with up-to-date and trustworthy healt...

Multimodal learning on graphs for disease relation extraction.

Journal of biomedical informatics
Disease knowledge graphs have emerged as a powerful tool for artificial intelligence to connect, organize, and access diverse information about diseases. Relations between disease concepts are often distributed across multiple datasets, including uns...

Leveraging AI tools to develop the writer rather than the writing.

Trends in ecology & evolution
Scientific writing can prove challenging, particularly for those who are non-native English speakers writing in English. Here, we explore the potential of advanced artificial intelligence (AI) tools, guided by principles of second-language acquisitio...