Matches in SemOpenAlex for { <https://semopenalex.org/work/W2566071823> ?p ?o ?g. }
Showing items 1 to 77 of
77
with 100 items per page.
- W2566071823 endingPage "101" @default.
- W2566071823 startingPage "100" @default.
- W2566071823 abstract "The pathogenesis of scoliosis progression remains poorly understood. Seventy-two subject data sets, consisting of four successive values of Cobb-angle and lateral deviations at apices for six and twelve-months intervals in the coronal plane, were used to train and test an artificial neural network (ANN) to predict spinal deformity progression. The accuracies of the trained ANN (3-4-1) for training and testing data were within 3.64° (±2.58°) and 4.40° (±1.86°) of Cobb angles, and within 3.59 (±3.96) mm and 3.98 (±3.41) mm of lateral deviations, respectively. The adapted technique for predicting the scoliosis deformity progression has promising clinical applications. Scoliosis is a common and poorly understood three-dimensional spinal deformity. The study purpose is to predict scoliosis progression at six and twelve months intervals in the future using successive spinal indices with an artificial neural network (ANN). The adapted ANN technique enables earlier detection of scoliosis progression with high accuracy. Improved prediction of scoliosis progression will impact bracing or surgical treatment decisions, and may decrease hazardous X-ray exposure. Seventy-two data sets from adolescent idiopathic scoliosis subjects recruited at the Alberta Children’s Hospital were used in this study. Data sets composed of four successive values of Cobb angles and lateral deviations at apices for six and twelvemonth intervals (coronal plane) were extracted to train and test a specific ANN for predicting scoliosis progression. Progression patterns in Cobb angles (n = 10) and lateral deviations (n = 8) were successfully identified. The accuracies of the trained ANN (3-4-1) with the training and testing data sets were 3.64° (±2.58°) and 4.40° (±1.86°) of Cobb angles, 3.59 (±3.96) mm and 3.98 (±3.41) mm of lateral deviations, respectively. These results are in close agreement with those using cubic spline extrapolation techniques (3.49° ± 1.85° and 3.31 ± 4.22 mm) and adaptive neuro-fuzzy inference system (3.92° ±3.53° and 3.37 ±3.95 mm) for the same testing data. ANN can be a promising technique for prediction of scoliosis progression with substantial improvements in accuracy over current techniques, leading to potentially important implications for scoliosis monitoring and treatment decisions. Funding: AHFMR, CIHR, Fraternal Order of Eagles, NSERC, GEOIDE." @default.
- W2566071823 created "2017-01-06" @default.
- W2566071823 creator A5004652265 @default.
- W2566071823 creator A5008740845 @default.
- W2566071823 creator A5044014365 @default.
- W2566071823 creator A5059205436 @default.
- W2566071823 creator A5068927267 @default.
- W2566071823 creator A5070654775 @default.
- W2566071823 creator A5084365145 @default.
- W2566071823 date "2008-03-01" @default.
- W2566071823 modified "2023-09-27" @default.
- W2566071823 title "PREDICTION OF SCOLIOSIS PROGRESSION IN TIME SERIES USING ARTIFICIAL INTELLIGENCE TECHNIQUES" @default.
- W2566071823 hasPublicationYear "2008" @default.
- W2566071823 type Work @default.
- W2566071823 sameAs 2566071823 @default.
- W2566071823 citedByCount "0" @default.
- W2566071823 crossrefType "journal-article" @default.
- W2566071823 hasAuthorship W2566071823A5004652265 @default.
- W2566071823 hasAuthorship W2566071823A5008740845 @default.
- W2566071823 hasAuthorship W2566071823A5044014365 @default.
- W2566071823 hasAuthorship W2566071823A5059205436 @default.
- W2566071823 hasAuthorship W2566071823A5068927267 @default.
- W2566071823 hasAuthorship W2566071823A5070654775 @default.
- W2566071823 hasAuthorship W2566071823A5084365145 @default.
- W2566071823 hasConcept C105702510 @default.
- W2566071823 hasConcept C13483470 @default.
- W2566071823 hasConcept C141071460 @default.
- W2566071823 hasConcept C2775946787 @default.
- W2566071823 hasConcept C2778871979 @default.
- W2566071823 hasConcept C2779982284 @default.
- W2566071823 hasConcept C2780811821 @default.
- W2566071823 hasConcept C2780955175 @default.
- W2566071823 hasConcept C29694066 @default.
- W2566071823 hasConcept C54355233 @default.
- W2566071823 hasConcept C71924100 @default.
- W2566071823 hasConcept C86803240 @default.
- W2566071823 hasConceptScore W2566071823C105702510 @default.
- W2566071823 hasConceptScore W2566071823C13483470 @default.
- W2566071823 hasConceptScore W2566071823C141071460 @default.
- W2566071823 hasConceptScore W2566071823C2775946787 @default.
- W2566071823 hasConceptScore W2566071823C2778871979 @default.
- W2566071823 hasConceptScore W2566071823C2779982284 @default.
- W2566071823 hasConceptScore W2566071823C2780811821 @default.
- W2566071823 hasConceptScore W2566071823C2780955175 @default.
- W2566071823 hasConceptScore W2566071823C29694066 @default.
- W2566071823 hasConceptScore W2566071823C54355233 @default.
- W2566071823 hasConceptScore W2566071823C71924100 @default.
- W2566071823 hasConceptScore W2566071823C86803240 @default.
- W2566071823 hasLocation W25660718231 @default.
- W2566071823 hasOpenAccess W2566071823 @default.
- W2566071823 hasPrimaryLocation W25660718231 @default.
- W2566071823 hasRelatedWork W1757881324 @default.
- W2566071823 hasRelatedWork W1784231194 @default.
- W2566071823 hasRelatedWork W1931195672 @default.
- W2566071823 hasRelatedWork W1964852088 @default.
- W2566071823 hasRelatedWork W1972603086 @default.
- W2566071823 hasRelatedWork W1985928689 @default.
- W2566071823 hasRelatedWork W1997016764 @default.
- W2566071823 hasRelatedWork W2021288269 @default.
- W2566071823 hasRelatedWork W2079909680 @default.
- W2566071823 hasRelatedWork W2142568044 @default.
- W2566071823 hasRelatedWork W2409542335 @default.
- W2566071823 hasRelatedWork W2442775009 @default.
- W2566071823 hasRelatedWork W2529604570 @default.
- W2566071823 hasRelatedWork W2766246241 @default.
- W2566071823 hasRelatedWork W2785423477 @default.
- W2566071823 hasRelatedWork W2964203038 @default.
- W2566071823 hasRelatedWork W2974597284 @default.
- W2566071823 hasRelatedWork W3035458475 @default.
- W2566071823 hasRelatedWork W3081958385 @default.
- W2566071823 hasRelatedWork W3173524502 @default.
- W2566071823 isParatext "false" @default.
- W2566071823 isRetracted "false" @default.
- W2566071823 magId "2566071823" @default.
- W2566071823 workType "article" @default.