Cargando…
MRI-based deep learning can discriminate between temporal lobe epilepsy, Alzheimer’s disease, and healthy controls
BACKGROUND: Radiological identification of temporal lobe epilepsy (TLE) is crucial for diagnosis and treatment planning. TLE neuroimaging abnormalities are pervasive at the group level, but they can be subtle and difficult to identify by visual inspection of individual scans, prompting applications...
Autores principales: | Chang, Allen J., Roth, Rebecca, Bougioukli, Eleni, Ruber, Theodor, Keller, Simon S., Drane, Daniel L., Gross, Robert E., Welsh, James, Abrol, Anees, Calhoun, Vince, Karakis, Ioannis, Kaestner, Erik, Weber, Bernd, McDonald, Carrie, Gleichgerrcht, Ezequiel, Bonilha, Leonardo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9970972/ https://www.ncbi.nlm.nih.gov/pubmed/36849746 http://dx.doi.org/10.1038/s43856-023-00262-4 |
Ejemplares similares
-
Radiological identification of temporal lobe epilepsy using
artificial intelligence: a feasibility study
por: Gleichgerrcht, Ezequiel, et al.
Publicado: (2021) -
The white matter connectome as an individualized biomarker of language impairment in temporal lobe epilepsy
por: Kaestner, Erik, et al.
Publicado: (2019) -
Language, Memory and the Temporal Lobes
por: Manes, Facundo, et al.
Publicado: (2011) -
Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning
por: Abrol, Anees, et al.
Publicado: (2021) -
Cognitive phenotypes in frontal lobe epilepsy
por: Arrotta, Kayela, et al.
Publicado: (2022)