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| Content Provider | ACM Digital Library |
|---|---|
| Author | Freitas, Andre Decker, Stefan Sahay, Ratnesh Jares, Joao Khan, Yasar Mehdi, Muntazir |
| Abstract | Biosimulation models have been recently introduced to understand the exact causative factors that give rise to impairment in human organs. Finite Element Method (FEM) provides a mathematical framework to simulate dynamic biological systems, with applications ranging from human ear, cardiovascular, to neurovascular research. Due to lack of a well-integrated data infrastructure, the steps involved in the execution and comparative evaluation of large Finite Element (FE) simulations are time consuming and are performed in isolated environments. In this paper, we present a Linked Data platform to improve the automation in integration, analysis and visualisation of biosimulation models for the inner-ear (cochlea) mechanics. The proposed platform aims to help domain scientists and clinicians for exploring and analysing Finite Element (FE) numerical data and simulation results obtained from multiple domains such as biological, geometrical, mathematical, physical models. We validate the platform by conducting a qualitative survey and perform quantitative experiments to record overall performance. |
| Starting Page | 89 |
| Ending Page | 96 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781450334624 |
| DOI | 10.1145/2814864.2814884 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-09-16 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Biosimulation Finite element method Healthcare and life sciences (hcls) Linked data Reference architecture |
| Content Type | Text |
| Resource Type | Article |
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