Introduction and objective:
In the last few years, an increase has been observed in the importance of artificial intelligence in different areas of life, industry, science and everyday processes, and its use has become easy and common, with a noticeable upward trend. As a result, artificial intelligence has also started to be used in medical science. The aim of the study was review of literature on Stethome artificial intelligence, which will allow the optimisation of the methodology in a planned study using the StethoMe stethoscope for remote monitoring of the effect of air pollution on the respiratory system.

Brief description of the state of knowledge:
The artificial intelligence algorithm integrated into the StethoMe electronic stethoscope is a tool that achieves high effectiveness in the process of recognising and classifying pathological respiratory murmurs. It performs very well in analysing their intensity. In the literature review no reports were found that StethoMe had already been used to detect exacerbations in chronic respiratory diseases correlated with air pollution. The scope of problems concerning the StethoMe artificial intelligence algorithm is relatively new, so there are few studies and publications on the subject.

Summary:
The use of an AI algorithm to monitor patients› respiratory murmurs over several months using StethoMe and comparing this data with information on the air quality in the patients› environment will enable an in-depth and innovative analysis of these relationships. In addition, this solution can aid auscultatory diagnosis by reducing the subjective assessment of the physician, reduce the number of inpatient visits, and aid in the monitoring of chronic diseases. StethoMe can improve out-of-hospital surveillance of individual patients, but it also seems to create opportunities for planning broader epidemiological studies.