Back to Search Start Over

Neuroimaging and machine learning for studying the pathways from mild cognitive impairment to Alzheimer's disease: A systematic review

Authors :
Maryam Ahmadzadeh
Gregory J. Christie
Theodore D. Cosco
Ali Arab
Mehrdad Mansouri
Kevin R. Wagner
Steve DiPaola
Sylvain Moreno
Publication Year :
2022
Publisher :
Research Square Platform LLC, 2022.

Abstract

Background: This systematic review synthesizes the most recent neuroimaging procedures and machine learning approaches for the prediction of conversion from mild cognitive impairment to Alzheimer’s disease dementia. Methods: We systematically searched PubMed, SCOPUS, and Web of Science databases following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) systematic review guidelines. Results: Our search returned 2572 articles, 56 of which met the criteria for inclusion in the final selection. The multimodality framework and deep learning techniques showed a potential for predicting the conversion of MCI to AD dementia. Conclusion:Findings of this systematic review identified that the possibility of using neuroimaging data processed by advanced learning algorithms is promising for the prediction of AD progression. We also provided a detailed description of the challenges that researchers are faced along with future research directions. The protocol has been registered in the International Prospective Register of Systematic Reviews– CRD42019133402 and published in the Systematic Reviews journal.

Details

ISSN :
42019133
Database :
OpenAIRE
Accession number :
edsair.doi...........8cb31bbe0b096ea174d07cfa5ab6d749
Full Text :
https://doi.org/10.21203/rs.3.rs-1927287/v1