Estudo Avaliativo dos Biomarcadores Mais Influentes Para Doença de Alzheimer Com K-means e Floresta Aleatória

Abstract

Alzheimer’s is a neurodegenerative disease that is related not only to memory, but to impairment of other important mental functions. From this perspective, the health care sector has shown one of the largest increases in the amount of digital data, which has led to the emergence of different techniques for exploring and treating them. These technologies are of fundamental importance for the health professional to ensure more accurate diagnoses, in addition to optimizing time, reducing costs and choosing the best interventions in the clinical decision-making process. In addition to contributing to a broader understanding of information and detection of hidden patterns. Therefore, a machine learning model was proposed to identify the best functional biomarkers of cognitive response to Transcranial Direct Current Stimulation (tDCS) capable of differentiating responders and non-responders to treatment.