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Recognition and Classification of Facial Expression Using Artificial Intelligence As a Key of Early Detection in Neurological Disorders Publisher



Goudarzi N1, 4 ; Taheri Z1, 5 ; Nezhad Salari AM1, 6 ; Kazemzadeh K1, 2 ; Tafakhori A1, 2, 3
Authors
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Authors Affiliations
  1. 1. Network of Neurosurgery and Artificial Intelligence (NONAI), Universal Scientific Education and Research Network (USERN), Tehran, Iran
  2. 2. Iranian Center of Neurological Research, Neuroscience Institute, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, 1419733141, Iran
  3. 3. Department of Neurology, School of Medicine, Tehran University of Medical Sciences, Tehran, 1416634793, Iran
  4. 4. Student Research Committee, Faculty of Medicine, Qazvin University of Medical Sciences, Qazvin, 1985717413, Iran
  5. 5. Student Research Committee, Faculty of Pharmacy, Pharmaceutical Sciences Branch, Islamic Azad University (IAUPS), Tehran, 19395/1495, Iran
  6. 6. Student Research Committee, Bam University of Medical Sciences, Bam, 7661771967, Iran

Source: Reviews in the Neurosciences Published:2025


Abstract

The recognition and classification of facial expressions using artificial intelligence (AI) presents a promising avenue for early detection and monitoring of neurodegenerative disorders. This narrative review critically examines the current state of AI-driven facial expression analysis in the context of neurodegenerative diseases, such as Alzheimer’s and Parkinson’s. We discuss the potential of AI techniques, including deep learning and computer vision, to accurately interpret and categorize subtle changes in facial expressions associated with these pathological conditions. Furthermore, we explore the role of facial expression recognition as a noninvasive, cost-effective tool for screening, disease progression tracking, and personalized intervention in neurodegenerative disorders. The review also addresses the challenges, ethical considerations, and future prospects of integrating AI-based facial expression analysis into clinical practice for early intervention and improved quality of life for individuals at risk of or affected by neurodegenerative diseases. © 2025 Walter de Gruyter GmbH, Berlin/Boston.