Deformation prediction of mouse embryos in cell injection experiment by a feedforward artificial neural network

Abbasi, A. A ; Sharif University of Technology | 2011

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  1. Type of Document: Article
  2. DOI: 10.1115/DETC2011-47073
  3. Publisher: 2011
  4. Abstract:
  5. In this study, neural network models have been used to predict the mechanical behaviors of mouse embryos. In addition, sensitivity analysis has been carried out to investigate the influence of the significance of input parameters on the mechanical behavior of mouse embryos. In order to reach these purposes two neural network models have been implemented. Experimental data earlier deduced-by [Flückiger, M. (2004). Cell Membrane Mechanical Modeling for Microrobotic Cell Manipulation. Diploma Thesis, ETHZ Swiss Federal Institute of Technology, Zurich, WS03/04]-were collected to obtain training and test data for the neural network. The results of these investigations show that the correlation values of the test and training data sets are between0.9988 and 1.0000, which are in good agreement with the experimental observations
  6. Keywords:
  7. Cell injection ; Correlation value ; Deformation prediction ; Experimental data ; Experimental observation ; Feed-forward artificial neural networks ; Input parameter ; Mechanical behavior ; Mechanical modeling ; Microrobotic cell manipulation ; Mouse embryos ; Neural network model ; Swiss Federal Institute of Technology ; Test data ; Training data sets ; Cell membranes ; Cytology ; Design ; Mammals ; Mechanical engineering ; Molecular biology
  8. Source: Proceedings of the ASME Design Engineering Technical Conference, 28 August 2011 through 31 August 2011 ; Volume 2, Issue PARTS A AND B , August , 2011 , Pages 543-550 ; 9780791854792 (ISBN)
  9. URL: http://proceedings.asmedigitalcollection.asme.org/proceeding.aspx?articleid=1639527