English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We present a method to discover interesting brain regions in [18F]fluorodeoxyglucose positron emission tomography (PET) scans, showing also thebenefits when PET scans are in combined use with non-imaging variables. Thediscriminative brain regions facilitate a better understanding of Alzheimer'sdisease (AD) progression, and they can also be used for predicting conversionfrom mild cognitive impairment (MCI) to AD. A survival analysis(Cox regression)and infinite Gaussian mixture model (IGMM) are introduced to identify theinformative brain regions, which can be further used to make a prediction ofconversion (in two years) from MCI to AD using only the baseline PET scan.Further, the predictive accuracy can be enhanced when non-imaging variables areused together with identified informative brain voxels. The results suggestthat PET scan imaging data is more predictive than other non-imaging data,revealing even better performance when both imaging and non-imaging data arecombined.

Survival analysis, the infinite Gaussian mixture model, FDG-PET and non-imaging data in the prediction of progression from mild cognitive impairment