Research on Precision Medicine AI Algorithm for Neuro Immune Gastrointestinal Diseases based on Quantum Biochemistry and Computational Cancer Genetics.

Abstract

Objective: The objective of this study is to conduct network toxicology analysis based on smoking habits and develop a simpler and more effective toxicology product ingestion control system.

Background: Smoking behavior can affect the pathogenesis and prognosis of neuroimmune gastrointestinal diseases.

Aims: The purpose of developing tools to assist clinical practice is to avoid the harm of cigarettes to the human body.

Methods: Molecular dynamics method was used to elucidate the biophysical mechanism of TP53 gene mutation caused by harmful ingredients, and the signaling pathway of midbrain edge excitation was determined by molecular dynamics of nicotine and dopamine receptor D3. The possible involvement of nicotine in neuronal damage was determined through the molecular interaction between nicotine and ACHE. Molecular pathways were analyzed based on the aforementioned biological principles, developed artificial intelligence systems and brain computer interface systems.

Results: Several signaling pathways were elucidated, and effective AI algorithms were developed.

Conclusion: The accuracy of artificial intelligence systems is over 70%. This study provides clinical doctors with a new precision medicine strategy and tool to regulate patient behavior and reduce disease risk. Other: This project was approved by the Ethics Committee of Chifeng Cancer Hospital and reported to the WHO.