title: Prediction of metabolic syndrome using artificial neural network system based on clinical data including insulin resistance index and serum adiponectin.
abstract: OBJECTIVE
  This study aimed to predict the 6-year incidence of metabolic syndrome (MetS) using an artificial neural network (ANN) system and multiple logistic regression (MLR) analysis based on clinical factors, including the insulin resistance index calculated by homeostasis model assessment (HOMA-IR).
  
  
  METHODS
  Subjects were recruited from participants in annual health check-ups in both 2000 and 2006. A total of 410 Japanese male teachers and other workers at Keio University, 30-59 years of age at baseline, participated in this retrospective cohort study.
  
  
  METHODS
  Clinical parameters were randomly divided into a training dataset and a validation dataset, and the ANN system and MLR analysis were applied to predict individual incidences. The leave some out cross validation method was used for validation.
  
  
  RESULTS
  The sensitivity of the prediction was 0.27 for the MLR model and 0.93 for the ANN system, while specificities were 0.95 and 0.91, respectively. Sensitivity analysis employing the ANN system identified BMI, age, diastolic blood pressure, HDL-cholesterol, LDL-cholesterol and HOMA-IR as important predictors, suggesting these factors to be non-linearly related to the outcome.
  
  
  CONCLUSIONS
  We successfully predicted the 6-year incidence of MetS using an ANN system based on clinical data, including HOMA-IR and serum adiponectin, in Japanese male subjects.
authors: Health Center, School of Medicine, Keio University, 35 Shinanomachi, Tokyo 160-8582, Japan. hhirose@hc.cc.keio.ac.jp
authors: Hiroshi
authors: H
authors: Hirose
authors: Tetsuro
authors: T
authors: Takayama
authors: Shigenari
authors: S
authors: Hozawa
authors: Toshifumi
authors: T
authors: Hibi
authors: Ikuo
authors: I
authors: Saito
mesh_terms: D052242:Adiponectin / Q000097:blood; D000328:Adult; D044466:Asian People; D015992:Body Mass Index; D008076:Cholesterol, HDL / Q000097:blood; D008078:Cholesterol, LDL / Q000097:blood; D006801:Humans; D007333:Insulin Resistance; D007564:Japan; D016015:Logistic Models; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood* / Q000175:diagnosis*; D008875:Middle Aged; D008954:Models, Biological; D016571:Neural Networks, Computer; D011237:Predictive Value of Tests; D012189:Retrospective Studies
chemical_list: C499918:ADIPOQ protein, human; D052242:Adiponectin; D008076:Cholesterol, HDL; D008078:Cholesterol, LDL