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<div><p>This work aims to promote early and accurate diagnosis of Temporal Lobe Epilepsy (TLE) by developing state-of-the-art deep learning techniques, with the goal of minimizing the consequences of epilepsy on individuals and society. Current approaches for TLE detection have drawbacks...

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Main Author:	Hasim Khan (21647570) (author)
Other Authors:	Ahmed Ibrahim Alutaibi (21647573) (author), Ghanshyam G. Tejani (12757325) (author), Sunil Kumar Sharma (21647576) (author), Ahmad Raza Khan (4846549) (author), Fuzail Ahmad (716427) (author), Seyed Jalaleddin Mousavirad (7167818) (author)
Published:	2025
Subjects:	Biotechnology Cancer Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified unam mri dataset particular mri sequences new hybrid attention grey wolf optimization enhanced transformer network different patient groups 82 %, indicating temporal lobe epilepsy fuzzy possibilistic c aal segmentation framework fasf )</ p early tle diagnosis promote early accurate diagnosis 83 %, 61 %, xlink "> work aims weak cross tle detection thoroughly assessed suggested approach proposed using proposed model proposed method practical use onset zones moderate ability developing state current approaches aal labelling
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