Table 6 The indexes and results of effective evaluation

the concept layer

Ontology and attribute definition, relationship construction, concept layer framework

Positive aspects:

Accuracy, rationality, completeness, standardization

Areas for improvement:

Generality, effectiveness

Further standardize and refine the concept layer framework of the knowledge graph to ensure its generality and effectiveness.

the data layer

Data preprocessing, knowledge extraction, knowledge fusion, knowledge processing

Positive aspects:

Precision, accuracy, recall, F1

Areas for improvement:

Robustness, portability

Conduct additional experiments on multi-source data to optimize the model and enhance its robustness and generalization capabilities.

the application layer

Visualization analysis, data queries, assisted diagnosis

Positive aspects:

Visualization, structured presentation, accuracy, usability, user-friendliness

Areas for improvement:

Completeness, operability, aesthetics, practicality

Integrate other feature knowledge graphs (such as more detailed basic information, other breast cancer examination data, breast cancer malignancy information), and suggest utilizing machine learning or deep learning for knowledge inference to improve the clinical application of the model.