Exploring Huntington's Disease Diagnosis via Artificial Intelligence Models: A Comprehensive Review

被引：16

作者：

Ganesh, Sowmiyalakshmi ^{[1
]}

Chithambaram, Thillai ^{[1
]}

Krishnan, Nadesh Ramu ^{[2
]}

Vincent, Durai Raj ^{[2
]}

Kaliappan, Jayakumar ^{[1
]}

Srinivasan, Kathiravan ^{[1
]}

机构：

[1] Vellore Inst Technol, Sch Comp Sci & Engn, Vellore 632014, Tamil Nadu, India

[2] Vellore Inst Technol, Sch Comp Sci Engn & Informat Syst, Vellore 632014, Tamil Nadu, India

来源：

DIAGNOSTICS | 2023年 / 13卷 / 23期

关键词：

Huntington's disease; Artificial Intelligence; machine learning; deep learning; diagnosis; RESTLESS LEGS SYNDROME; MOTOR SPEECH PATTERNS; REALITY TECHNOLOGY; CLASSIFICATION; BIOMARKERS; NEURODEGENERATION; FEATURES; SUPPORT;

D O I：

10.3390/diagnostics13233592

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

Huntington's Disease (HD) is a devastating neurodegenerative disorder characterized by progressive motor dysfunction, cognitive impairment, and psychiatric symptoms. The early and accurate diagnosis of HD is crucial for effective intervention and patient care. This comprehensive review provides a comprehensive overview of the utilization of Artificial Intelligence (AI) powered algorithms in the diagnosis of HD. This review systematically analyses the existing literature to identify key trends, methodologies, and challenges in this emerging field. It also highlights the potential of ML and DL approaches in automating HD diagnosis through the analysis of clinical, genetic, and neuroimaging data. This review also discusses the limitations and ethical considerations associated with these models and suggests future research directions aimed at improving the early detection and management of Huntington's disease. It also serves as a valuable resource for researchers, clinicians, and healthcare professionals interested in the intersection of machine learning and neurodegenerative disease diagnosis.

引用

页数：39

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