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• W3204459919 startingPage "2440" @default.
• W3204459919 abstract "The description of group-level, genotype- and phenotype-associated imaging traits is academically important, but the practical demands of clinical neurology centre on the accurate classification of individual patients into clinically relevant diagnostic, prognostic and phenotypic categories. Similarly, pharmaceutical trials require the precision stratification of participants based on quantitative measures. A single-centre study was conducted with a uniform imaging protocol to test the accuracy of an artificial neural network classification scheme on a cohort of 378 participants composed of patients with ALS, healthy subjects and disease controls. A comprehensive panel of cerebral volumetric measures, cortical indices and white matter integrity values were systematically retrieved from each participant and fed into a multilayer perceptron model. Data were partitioned into training and testing and receiver-operating characteristic curves were generated for the three study-groups. Area under the curve values were 0.930 for patients with ALS, 0.958 for disease controls, and 0.931 for healthy controls relying on all input imaging variables. The ranking of variables by classification importance revealed that white matter metrics were far more relevant than grey matter indices to classify single subjects. The model was further tested in a subset of patients scanned within 6 weeks of their diagnosis and an AUC of 0.915 was achieved. Our study indicates that individual subjects may be accurately categorised into diagnostic groups in an observer-independent classification framework based on multiparametric, spatially registered radiology data. The development and validation of viable computational models to interpret single imaging datasets are urgently required for a variety of clinical and clinical trial applications." @default.
• W3204459919 created "2021-10-11" @default.
• W3204459919 creator A5002878524 @default.
• W3204459919 creator A5030609927 @default.
• W3204459919 creator A5057078027 @default.
• W3204459919 date "2021-09-28" @default.
• W3204459919 modified "2023-09-30" @default.
• W3204459919 title "Pathological neural networks and artificial neural networks in ALS: diagnostic classification based on pathognomonic neuroimaging features" @default.
• W3204459919 cites W1547342827 @default.
• W3204459919 cites W1979447612 @default.
• W3204459919 cites W198796059 @default.
• W3204459919 cites W2009364004 @default.
• W3204459919 cites W2009837079 @default.
• W3204459919 cites W2010824802 @default.
• W3204459919 cites W2045319154 @default.
• W3204459919 cites W2081237186 @default.
• W3204459919 cites W2103755103 @default.
• W3204459919 cites W2110208125 @default.
• W3204459919 cites W2117920021 @default.
• W3204459919 cites W2127043436 @default.
• W3204459919 cites W2128552148 @default.
• W3204459919 cites W2136148445 @default.
• W3204459919 cites W2137687977 @default.
• W3204459919 cites W2143895814 @default.
• W3204459919 cites W2148828979 @default.
• W3204459919 cites W2154223956 @default.
• W3204459919 cites W2155221045 @default.
• W3204459919 cites W2226999535 @default.
• W3204459919 cites W2258395286 @default.
• W3204459919 cites W2293611291 @default.
• W3204459919 cites W2341025013 @default.
• W3204459919 cites W2345680560 @default.
• W3204459919 cites W2396017293 @default.
• W3204459919 cites W2513933507 @default.
• W3204459919 cites W2555857041 @default.
• W3204459919 cites W2558498169 @default.
• W3204459919 cites W2605599897 @default.
• W3204459919 cites W2622487635 @default.
• W3204459919 cites W2731899572 @default.
• W3204459919 cites W2745159796 @default.
• W3204459919 cites W2750107844 @default.
• W3204459919 cites W2767589013 @default.
• W3204459919 cites W2772970520 @default.
• W3204459919 cites W2773789615 @default.
• W3204459919 cites W2778854905 @default.
• W3204459919 cites W2784389648 @default.
• W3204459919 cites W2784982849 @default.
• W3204459919 cites W2789713147 @default.
• W3204459919 cites W2794051084 @default.
• W3204459919 cites W2797167914 @default.
• W3204459919 cites W2801425363 @default.
• W3204459919 cites W2875133760 @default.
• W3204459919 cites W2897459153 @default.
• W3204459919 cites W2898268106 @default.
• W3204459919 cites W2900624344 @default.
• W3204459919 cites W2903344422 @default.
• W3204459919 cites W2904172495 @default.
• W3204459919 cites W2910447392 @default.
• W3204459919 cites W2911326213 @default.
• W3204459919 cites W2918412837 @default.
• W3204459919 cites W2919525768 @default.
• W3204459919 cites W2924086781 @default.
• W3204459919 cites W2924231147 @default.
• W3204459919 cites W2928337083 @default.
• W3204459919 cites W2938579539 @default.
• W3204459919 cites W2948469016 @default.
• W3204459919 cites W2956926267 @default.
• W3204459919 cites W2958886051 @default.
• W3204459919 cites W2963034437 @default.
• W3204459919 cites W2965003023 @default.
• W3204459919 cites W2976358595 @default.
• W3204459919 cites W2977784403 @default.
• W3204459919 cites W2981465717 @default.
• W3204459919 cites W2984424697 @default.
• W3204459919 cites W3015510664 @default.
• W3204459919 cites W3031636042 @default.
• W3204459919 cites W3042898823 @default.
• W3204459919 cites W3044785410 @default.
• W3204459919 cites W3047794624 @default.
• W3204459919 cites W3049496146 @default.
• W3204459919 cites W3080444683 @default.
• W3204459919 cites W3083314580 @default.
• W3204459919 cites W3083955757 @default.
• W3204459919 cites W3095725651 @default.
• W3204459919 cites W3118495294 @default.
• W3204459919 cites W3119961199 @default.
• W3204459919 cites W3163001849 @default.
• W3204459919 cites W3175110976 @default.
• W3204459919 cites W3184510603 @default.
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• W3204459919 doi "https://doi.org/10.1007/s00415-021-10801-5" @default.
• W3204459919 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34585269" @default.
• W3204459919 hasPublicationYear "2021" @default.
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