Personalised Modelling on Integrated Clinical and EEG Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network System

被引：0

作者：

Doborjeh, Maryam Gholami ^{[1
]}

Kasabov, Nikola ^{[1
]}

机构：

[1] Auckland Univ Technol, Knowledge Engn & Discovery Res Inst, Auckland 1010, New Zealand

来源：

2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) | 2016年

关键词：

personalised modelling; spiking neural networks; NeuCube; spatiotemporal data; EEG data; opiate addict; methadone maintenance treatment;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper introduces a novel personalised modelling framework and system for analysing Spatio-Temporal Brain Data (STBD) along with person clinical static data. For every individual, based on selected subset of similar to this individual clinical data, a subset of STBD is used for training a personalised Spiking Neural Network (PSNN) model using the recently proposed NeuCube SNN architecture. The proposed method is illustrated on a case study of personalised modelling using clinical and EEG data of two groups of subjects - drug addicts and addicts under medication. The PSNN models help to achieve a better classification accuracy compared to global SNN models or when using traditional AI methods. A PSNN model visualisation enables discovery of new knowledge about individual persons and to distinguish complex STBD across subjects.

引用

页码：1373 / 1378

页数：6