FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4308965212> ?p ?o ?g. }

• W4308965212 abstract "Although many studies have been conducted on machine learning (ML) models for Parkinson's disease (PD) prediction using neuroimaging and movement analyses, studies with large population-based datasets are limited. We aimed to propose PD prediction models using ML algorithms based on the National Health Insurance Service-Health Screening datasets. We selected individuals who participated in national health-screening programs > 5 times between 2002 and 2015. PD was defined based on the ICD-code (G20), and a matched cohort of individuals without PD was selected using a 1:1 random sampling method. Various ML algorithms were applied for PD prediction, and the performance of the prediction models was compared. Neural networks, gradient boosting machines, and random forest algorithms exhibited the best average prediction accuracy (average area under the receiver operating characteristic curve (AUC): 0.779, 0.766, and 0.731, respectively) among the algorithms validated in this study. The overall model performance metrics were higher in men than in women (AUC: 0.742 and 0.729, respectively). The most important factor for predicting PD occurrence was body mass index, followed by total cholesterol, glucose, hemoglobin, and blood pressure levels. Smoking and alcohol consumption (in men) and socioeconomic status, physical activity, and diabetes mellitus (in women) were highly correlated with the occurrence of PD. The proposed health-screening dataset-based PD prediction model using ML algorithms is readily applicable, produces validated results, and could be a useful option for PD prediction models." @default.
• W4308965212 created "2022-11-20" @default.
• W4308965212 creator A5000615161 @default.
• W4308965212 creator A5031988163 @default.
• W4308965212 creator A5045725030 @default.
• W4308965212 creator A5053856488 @default.
• W4308965212 creator A5074501297 @default.
• W4308965212 creator A5083191296 @default.
• W4308965212 creator A5085478037 @default.
• W4308965212 date "2022-11-14" @default.
• W4308965212 modified "2023-09-26" @default.
• W4308965212 title "Machine learning based risk prediction for Parkinson's disease with nationwide health screening data" @default.
• W4308965212 cites W1479935944 @default.
• W4308965212 cites W1831050183 @default.
• W4308965212 cites W2006617902 @default.
• W4308965212 cites W2008560062 @default.
• W4308965212 cites W2023356978 @default.
• W4308965212 cites W2025514142 @default.
• W4308965212 cites W2035560826 @default.
• W4308965212 cites W2041811868 @default.
• W4308965212 cites W2065331428 @default.
• W4308965212 cites W2067458758 @default.
• W4308965212 cites W2069574718 @default.
• W4308965212 cites W2085518652 @default.
• W4308965212 cites W2086353679 @default.
• W4308965212 cites W2094069121 @default.
• W4308965212 cites W2143481518 @default.
• W4308965212 cites W2145126338 @default.
• W4308965212 cites W2157594323 @default.
• W4308965212 cites W2170272023 @default.
• W4308965212 cites W2292012480 @default.
• W4308965212 cites W2333909660 @default.
• W4308965212 cites W2474575341 @default.
• W4308965212 cites W2602860077 @default.
• W4308965212 cites W2750826478 @default.
• W4308965212 cites W2757321799 @default.
• W4308965212 cites W2775131913 @default.
• W4308965212 cites W2794572638 @default.
• W4308965212 cites W2796381877 @default.
• W4308965212 cites W2888203792 @default.
• W4308965212 cites W2901755615 @default.
• W4308965212 cites W2907797392 @default.
• W4308965212 cites W2910814369 @default.
• W4308965212 cites W2912755574 @default.
• W4308965212 cites W2945170956 @default.
• W4308965212 cites W2953791151 @default.
• W4308965212 cites W2981027525 @default.
• W4308965212 cites W3001160947 @default.
• W4308965212 cites W3009252469 @default.
• W4308965212 cites W3039563353 @default.
• W4308965212 cites W3091514793 @default.
• W4308965212 cites W3158559908 @default.
• W4308965212 cites W3182598472 @default.
• W4308965212 cites W4226080656 @default.
• W4308965212 doi "https://doi.org/10.1038/s41598-022-24105-9" @default.
• W4308965212 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36376523" @default.
• W4308965212 hasPublicationYear "2022" @default.
• W4308965212 type Work @default.
• W4308965212 citedByCount "0" @default.
• W4308965212 crossrefType "journal-article" @default.
• W4308965212 hasAuthorship W4308965212A5000615161 @default.
• W4308965212 hasAuthorship W4308965212A5031988163 @default.
• W4308965212 hasAuthorship W4308965212A5045725030 @default.
• W4308965212 hasAuthorship W4308965212A5053856488 @default.
• W4308965212 hasAuthorship W4308965212A5074501297 @default.
• W4308965212 hasAuthorship W4308965212A5083191296 @default.
• W4308965212 hasAuthorship W4308965212A5085478037 @default.
• W4308965212 hasBestOaLocation W43089652121 @default.
• W4308965212 hasConcept C119857082 @default.
• W4308965212 hasConcept C126322002 @default.
• W4308965212 hasConcept C154945302 @default.
• W4308965212 hasConcept C169258074 @default.
• W4308965212 hasConcept C2780221984 @default.
• W4308965212 hasConcept C41008148 @default.
• W4308965212 hasConcept C45804977 @default.
• W4308965212 hasConcept C50644808 @default.
• W4308965212 hasConcept C58471807 @default.
• W4308965212 hasConcept C71924100 @default.
• W4308965212 hasConceptScore W4308965212C119857082 @default.
• W4308965212 hasConceptScore W4308965212C126322002 @default.
• W4308965212 hasConceptScore W4308965212C154945302 @default.
• W4308965212 hasConceptScore W4308965212C169258074 @default.
• W4308965212 hasConceptScore W4308965212C2780221984 @default.
• W4308965212 hasConceptScore W4308965212C41008148 @default.
• W4308965212 hasConceptScore W4308965212C45804977 @default.
• W4308965212 hasConceptScore W4308965212C50644808 @default.
• W4308965212 hasConceptScore W4308965212C58471807 @default.
• W4308965212 hasConceptScore W4308965212C71924100 @default.
• W4308965212 hasFunder F4320322120 @default.
• W4308965212 hasIssue "1" @default.
• W4308965212 hasLocation W43089652121 @default.
• W4308965212 hasLocation W43089652122 @default.
• W4308965212 hasLocation W43089652123 @default.
• W4308965212 hasLocation W43089652124 @default.
• W4308965212 hasLocation W43089652125 @default.
• W4308965212 hasLocation W43089652126 @default.
• W4308965212 hasOpenAccess W4308965212 @default.
• W4308965212 hasPrimaryLocation W43089652121 @default.
• W4308965212 hasRelatedWork W2911455822 @default.
• W4308965212 hasRelatedWork W2987667774 @default.

• next