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Muath Alsuhaibani

3 papers hereh-index 346 citations6 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CL1
  • cs.CV1
  • cs.LG1

identity via Semantic Scholar / OpenAlex

most citedLinguistic-Based Mild Cognitive Impairment Detection Using Informative Loss

1 citations · 1 across the 1 of their papers we have counts for

collaborators

3 papers

cs.LG2024

A Review of Deep Learning Approaches for Non-Invasive Cognitive Impairment Detection

Muath Alsuhaibani, Ali Pourramezan Fard, Jian Sun +3

This review paper explores recent advances in deep learning approaches for non-invasive cognitive impairment detection. We examine various non-invasive indicators of cognitive decl…

cs.CL2024★ 1 cited

Linguistic-Based Mild Cognitive Impairment Detection Using Informative Loss

Ali Pourramezan Fard, Mohammad H. Mahoor, Muath Alsuhaibani +1

This paper presents a deep learning method using Natural Language Processing (NLP) techniques, to distinguish between Mild Cognitive Impairment (MCI) and Normal Cognitive (NC) cond…

cs.CV2023

Detection of Mild Cognitive Impairment Using Facial Features in Video Conversations

Muath Alsuhaibani, Hiroko H. Dodge, Mohammad H. Mahoor

Early detection of Mild Cognitive Impairment (MCI) leads to early interventions to slow the progression from MCI into dementia. Deep Learning (DL) algorithms could help achieve ear…

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