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Huntington Disease l: Introduction

Huntington Disease l: Introduction

Huntington disease or HD is a progressive, fatal neurodegenerative disorder inherited in an autosomal dominant pattern.PathophysiologyIt is caused by expansion of the CAG trinucleotide repeat in the HTT gene on chromosome 4 (4p16.3), producing an abnormal huntingtin protein with an expanded polyglutamine tract. This misfolded protein disrupts cellular function, leading to neuronal death. Normal alleles have ≤26 repeats, 27–35 are intermediate (risk of expansion), 36–39 show reduced penetrance,...

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

Sowmiyalakshmi Ganesh¹, Thillai Chithambaram¹, Nadesh Ramu Krishnan²

¹School of Computer Science and Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India.

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Summary

Artificial Intelligence (AI) shows promise for diagnosing Huntington's Disease (HD). Machine learning and deep learning algorithms can analyze diverse data to improve early detection and patient management.

Keywords:

Artificial Intelligence Huntington’s disease deep learning diagnosis machine learning

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Area of Science:

Neuroscience
Medical Informatics
Computational Biology

Background:

Huntington's Disease (HD) is a severe neurodegenerative disorder with motor, cognitive, and psychiatric symptoms.
Early and accurate diagnosis is critical for managing HD and improving patient outcomes.
Existing diagnostic methods can be invasive or time-consuming.

Purpose of the Study:

To review the application of Artificial Intelligence (AI) algorithms in diagnosing Huntington's Disease.
To identify trends, methodologies, and challenges in AI-driven HD diagnosis.
To highlight the potential of machine learning (ML) and deep learning (DL) for automated HD detection.

Main Methods:

Systematic review of existing literature on AI in HD diagnosis.
Analysis of studies utilizing clinical, genetic, and neuroimaging data.
Evaluation of ML and DL approaches for diagnostic accuracy.

Main Results:

AI, particularly ML and DL, demonstrates significant potential for automating Huntington's Disease diagnosis.
Analysis of multimodal data (clinical, genetic, neuroimaging) enhances diagnostic accuracy.
Identified key trends and methodologies in the application of AI for HD.

Conclusions:

AI-powered algorithms offer a promising avenue for the early and accurate diagnosis of Huntington's Disease.
Further research is needed to address limitations and ethical considerations for widespread clinical adoption.
This review serves as a resource for professionals at the intersection of AI and neurodegenerative disease research.