Abstract

The application of artificial intelligence in the analysis and identification of beneficial bacteria is an advanced field that contributes greatly to improving human health and understanding their environmental impacts. Artificial intelligence techniques, such as machine learning and big data analysis, enable the classification of beneficial bacteria and the study of their interaction with the human microbiome. Research indicates that these bacteria play a vital role in enhancing the immune system, preventing digestive and immune diseases, and improving overall health balance. Moreover, recent studies have shown that artificial intelligence can help identify beneficial bacteria strains that may contribute to the treatment of chronic diseases such as diabetes and heart disease, in addition to providing personalized solutions for the treatment of some immune disorders, as complex medical and microbiological data are analyzed to provide accurate results related to the impact of the microbiome on health.
    With regard to neurological diseases and cancer, artificial intelligence shows promising potential in determining how beneficial bacteria affect the growth of cancer cells as well as interacting with the nervous system in diseases such as Alzheimer's disease. The use of these techniques contributes to accelerating the discovery of microbial drugs and the development of new treatments.
Overall, it can be said that artificial intelligence represents a pivotal tool in enhancing a deep understanding of the health impact of beneficial bacteria, which contributes to the development of targeted and effective treatments, and opens new horizons in the medical and therapeutic field.