FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2034670014> ?p ?o ?g. }

• W2034670014 endingPage "401" @default.
• W2034670014 startingPage "386" @default.
• W2034670014 abstract "We propose a new method to maximize biomarker efficiency for detecting anatomical change over time in serial MRI. Drug trials using neuroimaging become prohibitively costly if vast numbers of subjects must be assessed, so it is vital to develop efficient measures of brain change. A popular measure of efficiency is the minimal sample size (n80) needed to detect 25% change in a biomarker, with 95% confidence and 80% power. For multivariate measures of brain change, we can directly optimize n80 based on a Linear Discriminant Analysis (LDA). Here we use a supervised learning framework to optimize n80, offering two alternative solutions. With a new medial surface modeling method, we track 3D dynamic changes in the lateral ventricles in 2065 ADNI scans. We apply our LDA-based weighting to the results. Our best average n80—in two-fold nested cross-validation—is 104 MCI subjects (95% CI: [94,139]) for a 1-year drug trial, and 75 AD subjects [64,102]. This compares favorably with other MRI analysis methods. The standard “statistical ROI” approach applied to the same ventricular surfaces requires 165 MCI or 94 AD subjects. At 2 years, the best LDA measure needs only 67 MCI and 52 AD subjects, versus 119 MCI and 80 AD subjects for the stat-ROI method. Our surface-based measures are unbiased: they give no artifactual additive atrophy over three time points. Our results suggest that statistical weighting may boost efficiency of drug trials that use brain maps." @default.
• W2034670014 created "2016-06-24" @default.
• W2034670014 creator A5005099850 @default.
• W2034670014 creator A5014949118 @default.
• W2034670014 creator A5030080763 @default.
• W2034670014 creator A5035768567 @default.
• W2034670014 creator A5043086041 @default.
• W2034670014 creator A5044611916 @default.
• W2034670014 creator A5065555086 @default.
• W2034670014 creator A5067131328 @default.
• W2034670014 creator A5069168079 @default.
• W2034670014 creator A5084339479 @default.
• W2034670014 date "2013-04-01" @default.
• W2034670014 modified "2023-10-16" @default.
• W2034670014 title "Maximizing power to track Alzheimer's disease and MCI progression by LDA-based weighting of longitudinal ventricular surface features" @default.
• W2034670014 cites W1757198209 @default.
• W2034670014 cites W1970928383 @default.
• W2034670014 cites W1971316923 @default.
• W2034670014 cites W1975900269 @default.
• W2034670014 cites W1977832043 @default.
• W2034670014 cites W1980046788 @default.
• W2034670014 cites W1982361270 @default.
• W2034670014 cites W1987011701 @default.
• W2034670014 cites W1987687395 @default.
• W2034670014 cites W1992395739 @default.
• W2034670014 cites W1997654188 @default.
• W2034670014 cites W2008152557 @default.
• W2034670014 cites W2012444972 @default.
• W2034670014 cites W2014294278 @default.
• W2034670014 cites W2015904620 @default.
• W2034670014 cites W2017516371 @default.
• W2034670014 cites W2027647533 @default.
• W2034670014 cites W2028739995 @default.
• W2034670014 cites W2028942474 @default.
• W2034670014 cites W2030840329 @default.
• W2034670014 cites W2034406508 @default.
• W2034670014 cites W2036903387 @default.
• W2034670014 cites W2040016992 @default.
• W2034670014 cites W2056543109 @default.
• W2034670014 cites W2056898461 @default.
• W2034670014 cites W2063859734 @default.
• W2034670014 cites W2078524519 @default.
• W2034670014 cites W2079484785 @default.
• W2034670014 cites W2080770218 @default.
• W2034670014 cites W2086683689 @default.
• W2034670014 cites W2088851552 @default.
• W2034670014 cites W2089371040 @default.
• W2034670014 cites W2095377654 @default.
• W2034670014 cites W2097440479 @default.
• W2034670014 cites W2099326256 @default.
• W2034670014 cites W2101730772 @default.
• W2034670014 cites W2105037799 @default.
• W2034670014 cites W2110208125 @default.
• W2034670014 cites W2111692402 @default.
• W2034670014 cites W2113588440 @default.
• W2034670014 cites W2115457642 @default.
• W2034670014 cites W2119000771 @default.
• W2034670014 cites W2126608837 @default.
• W2034670014 cites W2126776155 @default.
• W2034670014 cites W2139886607 @default.
• W2034670014 cites W2143792586 @default.
• W2034670014 cites W2144314866 @default.
• W2034670014 cites W2146089088 @default.
• W2034670014 cites W2150921243 @default.
• W2034670014 cites W2154778070 @default.
• W2034670014 cites W2155513557 @default.
• W2034670014 cites W2156220037 @default.
• W2034670014 cites W2157848968 @default.
• W2034670014 cites W2158728639 @default.
• W2034670014 cites W2163399942 @default.
• W2034670014 cites W2164378919 @default.
• W2034670014 cites W2165840723 @default.
• W2034670014 cites W2167638846 @default.
• W2034670014 cites W2169539372 @default.
• W2034670014 cites W2080985815 @default.
• W2034670014 doi "https://doi.org/10.1016/j.neuroimage.2012.12.052" @default.
• W2034670014 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3942253" @default.
• W2034670014 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/23296188" @default.
• W2034670014 hasPublicationYear "2013" @default.
• W2034670014 type Work @default.
• W2034670014 sameAs 2034670014 @default.
• W2034670014 citedByCount "56" @default.
• W2034670014 countsByYear W20346700142013 @default.
• W2034670014 countsByYear W20346700142014 @default.
• W2034670014 countsByYear W20346700142015 @default.
• W2034670014 countsByYear W20346700142016 @default.
• W2034670014 countsByYear W20346700142017 @default.
• W2034670014 countsByYear W20346700142018 @default.
• W2034670014 countsByYear W20346700142019 @default.
• W2034670014 countsByYear W20346700142020 @default.
• W2034670014 countsByYear W20346700142021 @default.
• W2034670014 countsByYear W20346700142022 @default.
• W2034670014 countsByYear W20346700142023 @default.
• W2034670014 crossrefType "journal-article" @default.
• W2034670014 hasAuthorship W2034670014A5005099850 @default.
• W2034670014 hasAuthorship W2034670014A5014949118 @default.
• W2034670014 hasAuthorship W2034670014A5030080763 @default.
• W2034670014 hasAuthorship W2034670014A5035768567 @default.

• next