Traditional Chinese Medicine often use the prescription composed of herbs to cure the disease, which requires doctors with the rich professional knowledge and experience. It is much expected that the prescription can be generated automatically to assist doctors in prescribing using such as machine learning on the tongue images. However, it is confronted with two challenges. First, there is not a larger tongue image database available for machine learning. Second, there is no such machine learning method available for generating prescription according to the given tongue image. This paper begins with constructing a larger tongue image database, where each image corresponds to a prescription. It then uses auto-encoder to extract features for the tongue image, on which the recommendation neural network is proposed to recommend herbs for the prescription. Finally, a new prescription generation method is proposed to select optimal herbs from the recommended herbs to form the final prescription. Experimental results on our constructed databases validate the effectiveness and the superior performance of the proposed methods.

中医通常使用由草药组成的处方来治愈疾病，这需要具有丰富专业知识和经验的医生。人们非常期望可以自动生成处方，以帮助医生开处方，例如在舌头图像上使用机器学习。但是，它面临两个挑战。首先，没有更大的舌头图像数据库可用于机器学习。其次，没有这样的机器学习方法可用于根据给定的舌头图像生成处方。本文从构建更大的舌头图像数据库开始，其中每个图像都对应一个处方。然后使用自动编码器提取舌头图像的特征，在其上建议神经网络建议为处方推荐草药。最后，提出了一种新的处方生成方法，可以从推荐的草药中选择最佳的草药以形成最终的处方。在我们构建的数据库上的实验结果验证了所提出方法的有效性和优越的性能。