Altered microcirculation in alzheimer’s disease assessed by machine learning applied to functional thermal imaging data

HIGHLIGHTS

SUMMARY

Alzheimer`s disease (AD) is a kind of dementia that mainly affects human memory abilities, and it is characterized by senile plaques, neurofibrillary tangles, and amyloid angiopathy. The data_analysis for IRT signals is generally based on time-domain data_analysis (e_g, differential or slope analysis) or frequency-based analysis. Approaches of machine_learning (ML) and deep learning (DL) have been proposed for the IRT signals` data_analysis to increase the capability of this technique to assess pathologies and autonomic activations. Of note, a recent review by Tanveer et_al describes how multiple ML approaches (e_g, SVM, artificial neural_network . . .

 



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