Bou Assi, Elie; Schindler, Kaspar; de Bézenac, Christophe; Denison, Timothy; Desai, Sharanya; Keller, Simon S; Lemoine, Émile; Rahimi, Abbas; Shoaran, Mahsa; Rummel, Christian (2023). From Basic Sciences and Engineering to Epileptology: A Translational Approach. Epilepsia, 64 Suppl 3, S72-S84. Wiley-Blackwell 10.1111/epi.17566
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Epilepsia_-_2023_-_Bou_Assi_-_From_Basic_Sciences_and_Engineering_to_Epileptology_A_Translational_Approach.pdf - Accepted Version Available under License Publisher holds Copyright. Download (2MB) | Preview |
Collaborative efforts between basic scientists, engineers, and clinicians are enabling translational epileptology. In this paper, we summarize recent advances presented at the International Conference for Technology and Analysis of Seizures (ICTALS 2022): 1) novel developments of structural magnetic resonance imaging; 2) latest electroencephalography signal processing applications; 3) big data for the development of clinical tools; 4) the emerging field of hyperdimensional computing; 5) the new generation of AI-enabled neuroprostheses; and 6) the use of collaborative platforms to facilitate epilepsy research translation. We highlight the promise of artificial intelligence reported in recent investigations and the need for multicenter data sharing initiatives.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology 04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurology |
UniBE Contributor: |
Schindler, Kaspar Anton, Rummel, Christian |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
0013-9580 |
Publisher: |
Wiley-Blackwell |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
06 Mar 2023 13:41 |
Last Modified: |
03 Mar 2024 00:25 |
Publisher DOI: |
10.1111/epi.17566 |
PubMed ID: |
36861368 |
Uncontrolled Keywords: |
Electroencephalography hyperdimensional computing intelligent neural prostheses magnetic resonance imaging scientific platforms |
BORIS DOI: |
10.48350/179462 |
URI: |
https://boris.unibe.ch/id/eprint/179462 |
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