Large language models are changing landscape of academic publications. A positive transformation?
Authors:
Martin Májovský; Martin Černý; David Netuka
Authors‘ workplace:
Neurochirurgická a neuroonkologická klinika 1. LF UK a ÚVN Praha
Published in:
Čas. Lék. čes. 2023; 162: 294-297
Category:
Review Article
Overview
The advent of large language models (LLMs) based on neural networks marks a significant shift in academic writing, particularly in medical sciences. These models, including OpenAI's GPT-4, Google's Bard, and Anthropic’s Claude, enable more efficient text processing through transformer architecture and attention mechanisms. LLMs can generate coherent texts that are indistinguishable from human-written content. In medicine, they can contribute to the automation of literature reviews, data extraction, and hypothesis formulation. However, ethical concerns arise regarding the quality and integrity of scientific publications and the risk of generating misleading content.
This article provides an overview of how LLMs are changing medical writing, the ethical dilemmas they bring, and the possibilities for detecting AI-generated text. It concludes with a focus on the potential future of LLMs in academic publishing and their impact on the medical community.
Keywords:
large language models (LLMs), neural networks, academic writing, artificial intelligence, transformer architecture, scientific research automation, publishing ethics, detection of AI-generated text
Sources
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Labels
Addictology Allergology and clinical immunology Angiology Audiology Clinical biochemistry Dermatology & STDs Paediatric gastroenterology Paediatric surgery Paediatric cardiology Paediatric neurology Paediatric ENT Paediatric psychiatry Paediatric rheumatology Diabetology Pharmacy Vascular surgery Pain managementArticle was published in
Journal of Czech Physicians
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