Applying Informatics in Tissue Engineering

Jie Xu; Xiaolin Zhou; Daping Yang; Haiyan Ge; Qi Wang; Kang Tu; Tiefang Guo

doi:10.1055/s-0038-1633921

Methods of Information in Medicine, Table of Contents

Methods Inf Med 2005; 44(01): 38-43
DOI: 10.1055/s-0038-1633921

Original Article

Schattauer GmbH

Applying Informatics in Tissue Engineering

Authors

Jie Xu

¹Department ofGeneral Surgery, The Shanghai Tenth People’s Hospital of Tongji University, Shanghai, P. R. China
Xiaolin Zhou

²Department of Neurology, The Shanghai First People’s Hospital of Shanghai Jiao Tong University, Shanghai, P. R. China
Daping Yang

³Department of Orthopaedics, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, P. R. China
Haiyan Ge

¹Department ofGeneral Surgery, The Shanghai Tenth People’s Hospital of Tongji University, Shanghai, P. R. China
Qi Wang

⁴Department of Bioinformatics, Harbin Medical University, Harbin, Heilongjiang, P. R. China
Kang Tu

⁴Department of Bioinformatics, Harbin Medical University, Harbin, Heilongjiang, P. R. China
Tiefang Guo

³Department of Orthopaedics, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, P. R. China

Abstract

Summary

Objective: To facilitate tissue engineering strategies determination with informatics tools.

Methods: Firstly, tissue engineering experimental data were standardized and integrated into a centralized database; secondly, we used data mining tools (e.g. artificial neural networks and decision trees) to predict the outcomes of tissue engineering strategies; thirdly, a strategy design algorithm was developed, and its efficacy was validated with animal experiments; lastly, we constructed an online database and a decision support system for tissue engineering.

Results: The artificial neural networks and the decision trees respectively predicted the outcomes of tissue engineering strategies with the predictive accuracy of 95.14% and 85.26%. Following the strategies generated by computer, we cured 18 of the 20 experimental animals with a significantly lower cost than usual.

Conclusion: Informatics is beneficial for realizing safe, effective and economical tissue engineering.

Keywords

Tissue engineering - informatics - database - artificial intelligence - machine learning

Full Text

References

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