Semantic Web-Based AI System for Neuroimmune-Gastrointestinal Medical Image Processing

At present, the medical field requires the development of clinical diagnostic and therapeutic robots. The research team successfully transformed the biophysical structures of mitochondria and lipid particles from 2D to 3D. Based on cloud point registration algorithm and SVM, LSSVM, and Bayesian algorithms, the predicted cloud point was added to the cloud point volume to increase the cloud point data capacity and combined with psychological analysis of 3D cloud point structure hierarchical clustering. The K-SVD algorithm is used to deconvolve pathological data to reduce color interference on visual transformers, fit 3D data of midbrain pathways, and finally fuse 2D data converted from pathological data, mandala data, and immune factor data with brain computer interface data for classification prediction, improving the robustness of artificial intelligence diagnostic algorithms. This information fusion robot can accurately diagnose the comprehensive condition of patients and contribute to medical assisted diagnosis.