Overview of machine learning algorithms application in Kazakhstan healthcare sector: analysis of existing solutions and their effectiveness

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.

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Publication Details

Published
2025-05-14
DOI
https://doi.org/10.1109/sist61657.2025.11139284
Primary Topic
Healthcare Systems and Public Health
Type
article
Field-Weighted Citation Impact
0.00
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article

Overview of machine learning algorithms application in Kazakhstan healthcare sector: analysis of existing solutions and their effectiveness

Alua Myrzakerimova, Pavel Tsoy
Healthcare Systems and Public Health
article

Overview of machine learning algorithms application in Kazakhstan healthcare sector: analysis of existing solutions and their effectiveness

Alua Myrzakerimova, Pavel Tsoy
article en

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.

Astana Medical University (KZ)
Openalex Percentile: Top 68%
Healthcare Systems and Public Health
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