Graph neural networks are one of the frontier technologies in artificial intelligence,with the powerful ability to process graph-structured data. In the field of traditional Chinesemedicine diagnosis and treatment,syndrome differentiation and treatment involves complex syndrome inference,prescription compatibility,etc.,which manifest as complex relationships of“disease-syndrome-symptom-prescription-medicine”,showing significant graph structure characteristics. This paper analyzed the graph structure characteristics of traditional Chinese medicine diagnosis and treatment data,discussed the graph structure transformation of traditional Chinese medicine diagnosis and treatment data and the application scenarios of traditional Chinese medicine graph neural network,and preliminarily explored the application ideas of graph neural network in the field of traditional Chinesemedicine. Applying graph neural networks to the field of traditional Chinesemedicine diagnosis and treatment requires modeling for different data types and application scenarios,solving initial graph construction,knowledge learning and features,etc.,and then providing support for downstream syndrome prediction,prescription recommendation,etc.
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |