Clinical Diagnosis and Treatment System for Neurological Psychological Gastrointestinal Diseases Based on Multimodal Artificial Intelligence and Immunology.

Objective: To predict and assist in the treatment of colorectal cancer.

Background: Precision medicine systems can provide strategy optimization for the diagnosis and treatment of colorectal cancer to meet the needs of clinical pricing institutions.

Aim: To design an artificial intelligence multimodal gastrointestinal disease clinical information system based on neuroimmune gene regulation.

Method: The system includes the use of cell gene expression levels to predict the 5-year survival rate of cancer patients, and the development of disease incidence rate prediction models based on immune cell status and living habits in somatic cell testing. The biological mechanism of feature selection in survival prediction systems was elucidated using single-cell sequencing technology, and this mechanism was analyzed in depth using molecular simulation techniques. Based on NCAM1 and CADM1 genes, biological activation pathway analysis was conducted to explore the biological mechanism of their synergistic immune genome regulation of gastrointestinal tumor proliferation.

Result: The accuracy of each model is higher than 0.70. The experimental credibility is high.

Conclusion: The research team conducted a detailed analysis of the biological characteristics of AI algorithms and reached a consensus with clinical experts. The ethical approval number of Chifeng Cancer Hospital is 202401, which has been reported by the World Health Organization.