Matches in SemOpenAlex for { <https://semopenalex.org/work/W936009743> ?p ?o ?g. }
Showing items 1 to 79 of
79
with 100 items per page.
- W936009743 abstract "Background: The purpose of this study was to develop an artificial neural networks (ANNs) model for predicting 2-year surgical satisfaction and compared with traditional predictive tool in LSCS patients. Materials and Methods: The two prediction models included an ANN model and a logistic regression (LR) model. The age, gender, duration of symptoms, walking distance, visual analog scale (VAS) of leg pain/numbness, the Japanese Orthopaedic Association (JOA) Score, the Neurogenic Claudication Outcome Score (NCOS) and the Stenosis Ratio (SR) values have been determined as the input variables for the developed ANNs and LR model. Patient surgical satisfaction was recorded by using standardized measure. ANNs were fed patient data in order to predict 2-year surgical satisfaction based on several input variables. Sensitivity analysis to the developed ANN model was applied to identify the important variables. The area under a receiver operating characteristic (ROC) curve (AUC), Hosmer-Lemeshow (H-L) statistics and accuracy rate were calculated for evaluating the two models. Results: A total of 168 (59 male, 109 female, mean age 59.8±11.6 years) patients were divided into training (n = 84), testing (n = 42), and validation (n = 42) data sets. Post-surgical satisfaction was 88.7% at 2-year follow-up. The SR was important variable selected by the ANN. The ANN model displayed better accuracy rate in 96.9% of patients, a better H-L statistic in 42.4% of patients, and a better AUC in 80.0% of patients, compared to the LR model. Conclusion: The findings show that an ANNs can predict 2-year surgical satisfaction for use in clinical application and more accurate compared to LR model. Normal 0 false false false EN-US X-NONE AR-SA /* Style Definitions */ table.MsoNormalTable{mso-style-name:Table Normal;mso-tstyle-rowband-size:0;mso-tstyle-colband-size:0;mso-style-noshow:yes;mso-style-priority:99;mso-style-qformat:yes;mso-style-parent:;mso-padding-alt:0cm 5.4pt 0cm 5.4pt;mso-para-margin:0cm;mso-para-margin-bottom:.0001pt;mso-pagination:widow-orphan;font-size:11.0pt;font-family:Calibri,sans-serif;mso-ascii-font-family:Calibri;mso-ascii-theme-font:minor-latin;mso-fareast-font-family:Times New Roman;mso-fareast-theme-font:minor-fareast;mso-hansi-font-family:Calibri;mso-hansi-theme-font:minor-latin;mso-bidi-font-family:Arial;mso-bidi-theme-font:minor-bidi;}" @default.
- W936009743 created "2016-06-24" @default.
- W936009743 creator A5014774447 @default.
- W936009743 creator A5021584383 @default.
- W936009743 creator A5048290272 @default.
- W936009743 creator A5066713121 @default.
- W936009743 creator A5072173476 @default.
- W936009743 date "2014-01-04" @default.
- W936009743 modified "2023-09-26" @default.
- W936009743 title "Prediction of Surgical Satisfaction in Patients with Lumbar Spinal Canal Stenosis Using Artificial Neural Networks" @default.
- W936009743 hasPublicationYear "2014" @default.
- W936009743 type Work @default.
- W936009743 sameAs 936009743 @default.
- W936009743 citedByCount "0" @default.
- W936009743 crossrefType "journal-article" @default.
- W936009743 hasAuthorship W936009743A5014774447 @default.
- W936009743 hasAuthorship W936009743A5021584383 @default.
- W936009743 hasAuthorship W936009743A5048290272 @default.
- W936009743 hasAuthorship W936009743A5066713121 @default.
- W936009743 hasAuthorship W936009743A5072173476 @default.
- W936009743 hasConcept C105795698 @default.
- W936009743 hasConcept C119857082 @default.
- W936009743 hasConcept C126322002 @default.
- W936009743 hasConcept C141071460 @default.
- W936009743 hasConcept C14184104 @default.
- W936009743 hasConcept C151956035 @default.
- W936009743 hasConcept C1862650 @default.
- W936009743 hasConcept C2779631646 @default.
- W936009743 hasConcept C2780175798 @default.
- W936009743 hasConcept C33923547 @default.
- W936009743 hasConcept C41008148 @default.
- W936009743 hasConcept C44575665 @default.
- W936009743 hasConcept C50644808 @default.
- W936009743 hasConcept C58471807 @default.
- W936009743 hasConcept C71924100 @default.
- W936009743 hasConcept C89128539 @default.
- W936009743 hasConceptScore W936009743C105795698 @default.
- W936009743 hasConceptScore W936009743C119857082 @default.
- W936009743 hasConceptScore W936009743C126322002 @default.
- W936009743 hasConceptScore W936009743C141071460 @default.
- W936009743 hasConceptScore W936009743C14184104 @default.
- W936009743 hasConceptScore W936009743C151956035 @default.
- W936009743 hasConceptScore W936009743C1862650 @default.
- W936009743 hasConceptScore W936009743C2779631646 @default.
- W936009743 hasConceptScore W936009743C2780175798 @default.
- W936009743 hasConceptScore W936009743C33923547 @default.
- W936009743 hasConceptScore W936009743C41008148 @default.
- W936009743 hasConceptScore W936009743C44575665 @default.
- W936009743 hasConceptScore W936009743C50644808 @default.
- W936009743 hasConceptScore W936009743C58471807 @default.
- W936009743 hasConceptScore W936009743C71924100 @default.
- W936009743 hasConceptScore W936009743C89128539 @default.
- W936009743 hasLocation W9360097431 @default.
- W936009743 hasOpenAccess W936009743 @default.
- W936009743 hasPrimaryLocation W9360097431 @default.
- W936009743 hasRelatedWork W1572792692 @default.
- W936009743 hasRelatedWork W162919465 @default.
- W936009743 hasRelatedWork W1991238884 @default.
- W936009743 hasRelatedWork W2010688601 @default.
- W936009743 hasRelatedWork W2015211126 @default.
- W936009743 hasRelatedWork W2020502126 @default.
- W936009743 hasRelatedWork W2021758087 @default.
- W936009743 hasRelatedWork W2057902044 @default.
- W936009743 hasRelatedWork W2067658292 @default.
- W936009743 hasRelatedWork W2076271897 @default.
- W936009743 hasRelatedWork W2078926658 @default.
- W936009743 hasRelatedWork W2085061114 @default.
- W936009743 hasRelatedWork W2095979858 @default.
- W936009743 hasRelatedWork W2102962027 @default.
- W936009743 hasRelatedWork W2104441823 @default.
- W936009743 hasRelatedWork W2128241607 @default.
- W936009743 hasRelatedWork W2130043895 @default.
- W936009743 hasRelatedWork W2131212205 @default.
- W936009743 hasRelatedWork W2155490978 @default.
- W936009743 hasRelatedWork W2368635860 @default.
- W936009743 isParatext "false" @default.
- W936009743 isRetracted "false" @default.
- W936009743 magId "936009743" @default.
- W936009743 workType "article" @default.