Artificial intelligence in epilepsy—applications and pathways to the clinic

A Lucas, A Revell, KA Davis - Nature Reviews Neurology, 2024 - nature.com
Artificial intelligence (AI) is rapidly transforming health care, and its applications in epilepsy
have increased exponentially over the past decade. Integration of AI into epilepsy …

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

E van Diessen, RA van Amerongen, M Zijlmans… - …, 2024 - Wiley Online Library
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 …

Predicting seizure recurrence from medical records using large language models

GK Mbizvo, I Buchan - The Lancet Digital Health, 2023 - thelancet.com
Epilepsy is a natural target for studying clinical prediction. The condition is characterised by
a lasting predisposition to spontaneous seizures. 2 The point at which a person is defined …

Advancing Real-time Pandemic Forecasting Using Large Language Models: A COVID-19 Case Study

H Du, J Zhao, Y Zhao, S Xu, X Lin, Y Chen… - arXiv preprint arXiv …, 2024 - arxiv.org
Forecasting the short-term spread of an ongoing disease outbreak is a formidable challenge
due to the complexity of contributing factors, some of which can be characterized through …

Extracting Epilepsy Patient Data with Llama 2

B Holgate, S Fang, A Shek, M McWilliam… - Proceedings of the …, 2024 - aclanthology.org
We fill a gap in scholarship by applying a generative Large Language Model (LLM) to
extract information from clinical free text about the frequency of seizures experienced by …

NeuroMorphix: A Novel Brain MRI Asymmetry-specific Feature Construction Approach For Seizure Recurrence Prediction

S Ghosh, V Vegh, S Moinian, H Moradi… - arXiv preprint arXiv …, 2024 - arxiv.org
Seizure recurrence is an important concern after an initial unprovoked seizure; without drug
treatment, it occurs within 2 years in 40-50% of cases. The decision to treat currently relies …

Advancing Real-time Pandemic Forecasting Using Large Language Models: A COVID-19 Case Study

HF Yang, H Du, J Zhao, Y Zhao, S Xu, X Lin, Y Chen… - 2024 - researchsquare.com
Forecasting the short-term spread of an ongoing disease outbreak is a formidable challenge
due to the complexity of contributing factors, some of which can be characterized through …