COMPARISON OF ARTIFICIAL INTELLIGENCE PERFORMANCES OBTAINED IN DATASET CLASSIFICATIONS USING RESPIRATORY DATA

Diagnosis of disease with respiratory data is very important today as it was in the past. These diagnoses, which are mostly based on human experience, have begun to leave their place to machines with the development of technology. Especially with the emergence of the COVID-19 epidemic, studies on the ability of artificial intelligence to diagnose diseases by using respiratory data have increased. Sharing open-source data has paved the way for studies on this subject. 
 
Artificial intelligence makes important contributions in many fields. In the field of health, significant success results have been obtained in studies on respiratory sounds. In this article, a literature review on respiratory sounds and artificial intelligence achievements was made. Databases in literature search; IEEE, Elsevier, Pubmed and Sciencedirect. As keywords, "breathing sounds and", "respiratory sound classification", together with "artificial intelligence" and "machine learning" were chosen. In the studies, 2010 and later were discussed. 
 
In this study, artificial intelligence methods used in 35 publications selected by literature review were compared in terms of the performances obtained in the training.