[bjective]This paper is about to expound the true meaning of the 374th clause of Treatise on Febrile Diseases. [Methods] Under the guidance of dynamic thinking of Treatise on Febrile Diseases, with the help of other clauses about Zaoshi syndrome, Small Decoction for Ordering the Qi, Gardenia and Prepared Soybean Decoction, to understand the 374th clause.[Results] The 374th clause is not alone, it should be combined with the 375th clause, they tell us when we treat the combination of Shi and Re syndrome of Yangming disease, we should use Small Decoction for Ordering the Qi first, then use Gardenia and Prepared Soybean Decoction. At the same time if we want to understand the 374th clause, we should combine it with the 368th clause to 375th clause, it tells us the treatment and difference between the diarrhea of cold, wet heat, Shi and Re, deficient heat etc. [Conclusion]This clause institutes the principle of the treatment for Shi and Re syndrome of Yangming disease, completing the system of treating diarrhea. It also tells us how to combine two decoctions.

Objective Traditional Chinese medicine tongue diagnosis plays an important role in the clinical diagnosis and treatment of diseases,but the current research results are not applicable to the evaluation of clinical efficacy.This study conducted a hierarchical quantitative study on tongue color based on hyperspectral data of tongue images,making it suitable for clinical efficacy evaluation.Methods Establish inclusion and exclusion criteria,obtain tongue images of different spectral wavelengths within the visible light range of 400-1000 nm,and use traditional Chinese medicine clinical experts to distinguish between red tongue and yellow coating in four different color levels(mild,moderate,severe,and severe).Finally,establish a quantitative prediction model for the grade of red tongue and yellow coating based on machine learning models.Results There were significant differences in hyperspectral curve characteristics between red tongue and yellow coating with different color levels,which could be used as the basis for grade quantification.With the help of principal component analysis+random forest model,85.79%and 88.34%of the red tongue and yellow coating with different color levels could be predicted.Conclusion The use of hyperspectral image data features and machine learning models for predicting different color levels of tongue color has achieved good accuracy.