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
