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Abstract
The aim of this study is to provide decision support with artificial intelligence for tendon tissue engineering strategies. The experimental data of tissue-engineered tendons were integrated and standardized with a centralized database, and a decision support system was developed using both artificial neural networks and decision trees. The decision support system was trained with existing cases in the database, and then was used to generate tissue engineering schemes for new experimental animals. Following the schemes generated by the artificial intelligent system, we cured 28 of the 30 experimental animals. In conclusion, artificial intelligence is a powerful method for decision support in the tendon tissue engineering realm.