| Title: |
Potential merits and flaws of large language models in epilepsy care:A critical review |
| Authors: |
van Diessen, Eric; van Amerongen, Ramon A.; Zijlmans, Maeike; Otte, Willem M.; Projectafdeling KIND; Brain; Neurologie |
| Publication Year: |
2024 |
| Subject Terms: |
diagnosing epilepsy; large language models; natural language processing; Neurology; Clinical Neurology; Journal Article; Review |
| Description: |
The 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. |
| Document Type: |
article in journal/newspaper |
| File Description: |
text/plain |
| Language: |
English |
| ISSN: |
0013-9580 |
| Relation: |
https://dspace.library.uu.nl/handle/1874/453514 |
| Availability: |
https://dspace.library.uu.nl/handle/1874/453514 |
| Rights: |
info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.FBA17B4F |
| Database: |
BASE |