MedVir: An Interactive Representation System of Multidimensional Medical Data Applied to Traumatic Brain Injury's Rehabilitation Prediction

被引：0

作者：

Gonzalez, Santiago ^{[1
]}

Gracia, Antonio ^{[1
]}

Herrero, Pilar ^{[1
]}

Castellanos, Nazareth ^{[2
]}

Paul, Nuria ^{[3
]}

机构：

[1] Univ Politecn Madrid, Sch Comp Sci, Madrid, Spain

[2] Univ Politecn Madrid, Ctr Biomed Technol, Madrid, Spain

[3] Univ Complutense Madrid, Dept Basic Psychol I, Madrid, Spain

来源：

ROUGH SETS AND INTELLIGENT SYSTEMS PARADIGMS, RSEISP 2014 | 2014年 / 8537卷

关键词：

dimensionality reduction; multivariate medical data; feature selection; data mining; visualization; interaction; virtual reality; TBI; MEG; VISUALIZATION; EXPLORATION; SELECTION;

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：

Clinicians could model the brain injury of a patient through his brain activity. However, how this model is defined and how it changes when the patient is recovering are questions yet unanswered. In this paper, the use of MedVir framework is proposed with the aim of answering these questions. Based on complex data mining techniques, this provides not only the differentiation between TBI patients and control subjects (with a 72% of accuracy using 0.632 Bootstrap validation), but also the ability to detect whether a patient may recover or not, and all of that in a quick and easy way through a visualization technique which allows interaction.

引用

页码：248 / 257

页数：10

共 31 条

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