• Technology Introduction

  Magnetic resonance imaging (MRI) images were acquired using a GE MR750 3T scanner. For each participant, a resting-state functional connectivity (RSFC) matrix was created from 8 minutes of resting-state functional MRI images. These matrices were entered as features into multivariate pattern analysis (MVPA), a machine learning technique, to predict an individual's age and his/her cognitive performance.
 

• Scientific Innovation

  This technique can accurately predict an individual's age and cognitive performance based on fast resting-state acquisition and multivariate analysis. Our current predictor has the second highest accuracy among published MRI-based age predictors around the world.
 

• This technology won the Futuretech Breakthrough Award in 2018 Future Tech Expo.
• Institutes
• National Cheng Kung University
  Shulan Hsieh/psyhsl@mail.ncku.edu.tw