FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4293217811> ?p ?o ?g. }

• W4293217811 endingPage "1369" @default.
• W4293217811 startingPage "1369" @default.
• W4293217811 abstract "Objectives: Abnormal dopamine transporter (DAT) uptake is an important biomarker for diagnosing Lewy body disease (LBD), including Parkinson’s disease (PD) and dementia with Lewy bodies (DLB). We evaluated a machine learning-derived visual scale (ML-VS) for Tc99m TRODAT-1 from one center and compared it with the striatal/background ratio (SBR) using semiquantification for diagnosing LBD in two other centers. Patients and Methods: This was a retrospective analysis of data from a history-based computerized dementia diagnostic system. MT-VS and SBR among normal controls (NCs) and patients with PD, PD with dementia (PDD), DLB, or Alzheimer’s disease (AD) were compared. Results: We included 715 individuals, including 122 NCs, 286 patients with PD, 40 with AD, 179 with DLB, and 88 with PDD. Compared with NCs, patients with PD exhibited a significantly higher prevalence of abnormal DAT uptake using all methods. Compared with the AD group, PDD and DLB groups exhibited a significantly higher prevalence of abnormal DAT uptake using all methods. The distribution of ML-VS was significantly different between PD and NC, DLB and AD, and PDD and AD groups (all p < 0.001). The correlation coefficient of ML-VS/SBR in all participants was 0.679. Conclusions: The ML-VS designed in one center is useful for differentiating PD from NC, DLB from AD, and PDD from AD in other centers. Its correlation with traditional approaches using different scanning machines is also acceptable. Future studies should develop models using data pools from multiple centers for increasing diagnostic accuracy." @default.
• W4293217811 created "2022-08-27" @default.
• W4293217811 creator A5012590464 @default.
• W4293217811 creator A5038473989 @default.
• W4293217811 creator A5046095365 @default.
• W4293217811 creator A5063649218 @default.
• W4293217811 creator A5075181003 @default.
• W4293217811 creator A5080107071 @default.
• W4293217811 date "2022-08-25" @default.
• W4293217811 modified "2023-09-25" @default.
• W4293217811 title "Real-World Testing of a Machine Learning–Derived Visual Scale for Tc99m TRODAT-1 for Diagnosing Lewy Body Disease: Comparison with a Traditional Approach Using Semiquantification" @default.
• W4293217811 cites W1985456042 @default.
• W4293217811 cites W1991952617 @default.
• W4293217811 cites W2003688643 @default.
• W4293217811 cites W2014636870 @default.
• W4293217811 cites W2015759096 @default.
• W4293217811 cites W2024849549 @default.
• W4293217811 cites W2040670498 @default.
• W4293217811 cites W2052966244 @default.
• W4293217811 cites W2065417201 @default.
• W4293217811 cites W2088610730 @default.
• W4293217811 cites W2096977656 @default.
• W4293217811 cites W2112455323 @default.
• W4293217811 cites W2115017507 @default.
• W4293217811 cites W2121179979 @default.
• W4293217811 cites W2124681501 @default.
• W4293217811 cites W2131092854 @default.
• W4293217811 cites W2151641755 @default.
• W4293217811 cites W2151736176 @default.
• W4293217811 cites W2166263576 @default.
• W4293217811 cites W2166609052 @default.
• W4293217811 cites W2167980887 @default.
• W4293217811 cites W2290432223 @default.
• W4293217811 cites W2342343026 @default.
• W4293217811 cites W2520511459 @default.
• W4293217811 cites W2623521763 @default.
• W4293217811 cites W2754039296 @default.
• W4293217811 cites W2768017870 @default.
• W4293217811 cites W2971256692 @default.
• W4293217811 cites W2996712863 @default.
• W4293217811 cites W3004231862 @default.
• W4293217811 cites W3009753279 @default.
• W4293217811 cites W3022310962 @default.
• W4293217811 cites W3106046505 @default.
• W4293217811 cites W3137124426 @default.
• W4293217811 cites W3195657824 @default.
• W4293217811 cites W3207875145 @default.
• W4293217811 cites W4200532886 @default.
• W4293217811 doi "https://doi.org/10.3390/jpm12091369" @default.
• W4293217811 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36143154" @default.
• W4293217811 hasPublicationYear "2022" @default.
• W4293217811 type Work @default.
• W4293217811 citedByCount "0" @default.
• W4293217811 crossrefType "journal-article" @default.
• W4293217811 hasAuthorship W4293217811A5012590464 @default.
• W4293217811 hasAuthorship W4293217811A5038473989 @default.
• W4293217811 hasAuthorship W4293217811A5046095365 @default.
• W4293217811 hasAuthorship W4293217811A5063649218 @default.
• W4293217811 hasAuthorship W4293217811A5075181003 @default.
• W4293217811 hasAuthorship W4293217811A5080107071 @default.
• W4293217811 hasBestOaLocation W42932178111 @default.
• W4293217811 hasConcept C117220453 @default.
• W4293217811 hasConcept C126322002 @default.
• W4293217811 hasConcept C137183658 @default.
• W4293217811 hasConcept C142724271 @default.
• W4293217811 hasConcept C15744967 @default.
• W4293217811 hasConcept C185592680 @default.
• W4293217811 hasConcept C2524010 @default.
• W4293217811 hasConcept C2776755682 @default.
• W4293217811 hasConcept C2778548049 @default.
• W4293217811 hasConcept C2779097696 @default.
• W4293217811 hasConcept C2779134260 @default.
• W4293217811 hasConcept C2779483572 @default.
• W4293217811 hasConcept C2779734285 @default.
• W4293217811 hasConcept C2781197716 @default.
• W4293217811 hasConcept C2989005 @default.
• W4293217811 hasConcept C3020647687 @default.
• W4293217811 hasConcept C33923547 @default.
• W4293217811 hasConcept C513476851 @default.
• W4293217811 hasConcept C55493867 @default.
• W4293217811 hasConcept C71924100 @default.
• W4293217811 hasConcept C90924648 @default.
• W4293217811 hasConceptScore W4293217811C117220453 @default.
• W4293217811 hasConceptScore W4293217811C126322002 @default.
• W4293217811 hasConceptScore W4293217811C137183658 @default.
• W4293217811 hasConceptScore W4293217811C142724271 @default.
• W4293217811 hasConceptScore W4293217811C15744967 @default.
• W4293217811 hasConceptScore W4293217811C185592680 @default.
• W4293217811 hasConceptScore W4293217811C2524010 @default.
• W4293217811 hasConceptScore W4293217811C2776755682 @default.
• W4293217811 hasConceptScore W4293217811C2778548049 @default.
• W4293217811 hasConceptScore W4293217811C2779097696 @default.
• W4293217811 hasConceptScore W4293217811C2779134260 @default.
• W4293217811 hasConceptScore W4293217811C2779483572 @default.
• W4293217811 hasConceptScore W4293217811C2779734285 @default.
• W4293217811 hasConceptScore W4293217811C2781197716 @default.
• W4293217811 hasConceptScore W4293217811C2989005 @default.
• W4293217811 hasConceptScore W4293217811C3020647687 @default.

• next