Research on Chinese Medicine Autism Diagnosis and Treatment Aid System Based on Artificial Intelligence

It would be worthwhile to explore research in applying advanced technologies in the process of improving patient care due to the uniqueness of the challenges involved in diagnosis and treatment of autism using Chinese medicine. This paper discusses the Artificial Intelligence-aided Enhancement of a Chinese Medicine Autism Diagnosis and Treatment Support System. First, compilation of the feature data of patients diagnosed with autism was done. Then rigorous data preprocessing, including handling strategies for missing values and data normalization, was carried out. We did the correlation analysis to understand how features are interrelated. This was followed by PCA-based dimensionality reduction, whereby we reduced the model's complexity and obtained important features. Further, these reduced features were used to train traditional machine learning methods: decision trees, support vector machines, and random forests. A comparative study showed that the decision tree model was better than others with respect to accuracy, precision, recall, and the F1 score. It also applied visualization techniques to explain the inner working of the model, hence making it more interpretable. This paper concludes that a combination of Artificial Intelligence with diagnosis and treatment in Chinese Medicine has the potential to provide comprehensive and accurate medical services related to autism, hence developing healthcare in this regard.