Cargando…
Clinical Application of Machine Learning Models for Brain Imaging in Epilepsy: A Review
Epilepsy is a common neurological disorder characterized by recurrent and disabling seizures. An increasing number of clinical and experimental applications of machine learning (ML) methods for epilepsy and other neurological and psychiatric disorders are available. ML methods have the potential to...
Autores principales: | Sone, Daichi, Beheshti, Iman |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8258163/ https://www.ncbi.nlm.nih.gov/pubmed/34239413 http://dx.doi.org/10.3389/fnins.2021.684825 |
Ejemplares similares
-
Comparing CAT12 and VBM8 for Detecting Brain Morphological Abnormalities in Temporal Lobe Epilepsy
por: Farokhian, Farnaz, et al.
Publicado: (2017) -
Gray Matter and White Matter Abnormalities in Temporal Lobe Epilepsy Patients with and without Hippocampal Sclerosis
por: Beheshti, Iman, et al.
Publicado: (2018) -
FLAIR-Wise Machine-Learning Classification and Lateralization of MRI-Negative (18)F-FDG PET-Positive Temporal Lobe Epilepsy
por: Beheshti, Iman, et al.
Publicado: (2020) -
Neuroimaging-Based Brain Age Estimation: A Promising Personalized Biomarker in Neuropsychiatry
por: Sone, Daichi, et al.
Publicado: (2022) -
Making the Invisible Visible: Advanced Neuroimaging Techniques in Focal Epilepsy
por: Sone, Daichi
Publicado: (2021)