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Machine learning for prediction of Alzheimer's Disease using brain diffusion tensor imaging

Grant number: 21/09205-0
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): November 01, 2021
Effective date (End): August 31, 2022
Field of knowledge:Health Sciences - Medicine
Principal researcher:Liara Rizzi
Grantee:Thais Maria Santos Bezerra
Home Institution: Faculdade de Ciências Médicas (FCM). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

Alzheimer's disease is the main cause of age-related dementia. One of its main current challenges consists in expanding diagnostic capacities in order to early identify the disease, preferably by using non-invasive methods. Parameters extracted by novel neuroimaging techniques including diffusion tensor imaging show promising results in the discrimination of AD's characteristics. In view of that, the current project aims to understand the diagnostic capacity of diffusion tensor imaging utilizing machine learning techniques to distinguish, among patients with mild cognitive impairment, which are more likely to progress to AD dementia. The neuroimaging parameters were collected from patients followed at Neuropsicology and Dementia's ambulatory of Hospital de Clínicas da UNICAMP and machine learning analyses will be performed using Python 3.0. (AU)

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