Potential merits and flaws of large language models in epilepsy care: A critical review

Author:

van Diessen Eric12ORCID,van Amerongen Ramon A.3,Zijlmans Maeike45ORCID,Otte Willem M.1ORCID

Affiliation:

1. Department of Child Neurology, UMC Utrecht Brain Center University Medical Center Utrecht and Utrecht University Utrecht The Netherlands

2. Department of Pediatrics Franciscus Gasthuis & Vlietland Rotterdam The Netherlands

3. Faculty of Science, Bioinformatics and Biocomplexity Utrecht University Utrecht The Netherlands

4. Department of Neurology and Neurosurgery, UMC Utrecht Brain Center University Medical Center Utrecht and Utrecht University Utrecht The Netherlands

5. Stichting Epilepsie Instellingen Nederland Heemstede The Netherlands

Abstract

AbstractThe current pace of development and applications of large language models (LLMs) is unprecedented and will impact future medical care significantly. In this critical review, we provide the background to better understand these novel artificial intelligence (AI) models and how LLMs can be of future use in the daily care of people with epilepsy. Considering the importance of clinical history taking in diagnosing and monitoring epilepsy—combined with the established use of electronic health records—a great potential exists to integrate LLMs in epilepsy care. We present the current available LLM studies in epilepsy. Furthermore, we highlight and compare the most commonly used LLMs and elaborate on how these models can be applied in epilepsy. We further discuss important drawbacks and risks of LLMs, and we provide recommendations for overcoming these limitations.

Publisher

Wiley

Reference84 articles.

1. Attention is all you need;Vaswani A;Adv Neural Inf Proces Syst,2017

2. Training language models to follow instructions with human feedback;Ouyang L;Adv Neural Inf Proces Syst,2022

3. Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum

4. ChatGPT and Other Large Language Models Are Double-edged Swords

5. Using ChatGPT to write patient clinic letters

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