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September 16, 2025SpringerOpen Access

Graph-theoretical mapping of cortical and subcortical network alterations in preclinical neurodegeneration

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This review evaluates network metrics and machine learning models for identifying neurodegenerative changes, suggesting improved diagnostic methods.

Structural network alterations are observed in preclinical stages of Alzheimer's disease, Parkinson's disease, and small vessel disease.
Machine learning models, including SVM and RF, achieved classification accuracies up to 93%, enhancing early diagnosis potential.
Key network features, such as global efficiency and path length, correlate with cognitive scores, indicating their relevance in neurodegenerative conditions.
Inconsistencies in data harmonization methods across studies may affect reproducibility, highlighting the need for standardized protocols.

Eren Öğüt (2025) studied this question.

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September 16, 2025SpringerOpen Access

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Authors

This review evaluates network metrics and machine learning models for identifying neurodegenerative changes, suggesting improved diagnostic methods.

Structural network alterations are observed in preclinical stages of Alzheimer's disease, Parkinson's disease, and small vessel disease.
Machine learning models, including SVM and RF, achieved classification accuracies up to 93%, enhancing early diagnosis potential.
Key network features, such as global efficiency and path length, correlate with cognitive scores, indicating their relevance in neurodegenerative conditions.
Inconsistencies in data harmonization methods across studies may affect reproducibility, highlighting the need for standardized protocols.

Eren Öğüt (2025) studied this question.

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