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

Santiago Gonzalez, Antonio Gracia, Pilar Herrero, Nazareth Castellanos, Nuria Paul
<span title="">2014</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
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
more &raquo; ... 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.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-08729-0_24">doi:10.1007/978-3-319-08729-0_24</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iaoc4naeorbflcm2g75arp46km">fatcat:iaoc4naeorbflcm2g75arp46km</a> </span>
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