The application of machine learning on brain imaging features of different narcolepsy subtypes.

Wei-Chih ChinSheng-Yao HuangFeng-Yuan LiuChih-Huan WangI TangIng-Tsung HsiaoYu-Shu Huang

Published in: Sleep (2024)

The accuracy of our predictive model of PET data are promising and can aid clinicians in the diagnosis of narcolepsy subtypes. Future research with a larger sample size could further refine the predictive model of narcolepsy.

Keyphrases

machine learning
big data
high resolution
computed tomography
palliative care
artificial intelligence
white matter
current status
brain injury
pet imaging
subarachnoid hemorrhage
photodynamic therapy
fluorescence imaging
data analysis