Abstract
This study analyzes machine learning algorithms for disease diagnosis based on chest X-ray images, with a focus on their use in Kazakhstan's healthcare industry. It intends to investigate the efficacy of contemporary pre-trained machine learning models in medical image analysis to precisely identify a range of disease classifications connected to the chest. The merits, drawbacks, and potential for integration into regional medical practices of the machine learning technologies now in use in the healthcare industry are all highlighted in this thorough review. The study also includes evaluating and comparing existing models to identify the most suitable solution based on specific metrics such as accuracy, efficiency and ease of use. The ultimate objective is to assist medical professionals in making data-driven decisions for better patient outcomes and to help improve diagnostic procedures.