The following is a summary of “Neuroimaging and machine learning for studying the pathways from mild cognitive impairment to alzheimer’s disease: a systematic review,” published in the August 2023 issue of Neurology by Ahmadzadeh et al.
Researchers performed a systematic review of the latest neuroimaging and machine learning methods for predicting Alzheimer’s disease dementia conversion from mild cognitive impairment.
They conducted their search in accordance with the systematic review guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The search encompassed PubMed, SCOPUS, and Web of Science databases.
The results showed that out of 2,572 articles, 56 fulfilled the inclusion criteria. The potential was observed using a multimodality framework and deep learning for predicting MCI to AD dementia conversion.
They concluded the potential of utilizing neuroimaging data and advanced learning algorithms for predicting AD progression. Challenges faced by researchers and future research directions were outlined. The protocol was registered as CRD42019133402 and published in the Systematic Reviews journal.
Source: bmcneurol.biomedcentral.com/articles/10.1186/s12883-023-03323-2
