MONITORING THE SPREAD OF HOSPITAL INFECTIONS USING ARTIFICIAL INTELLIGENCE

Authors

  • Nafosatkhon Khayrullokhonova Tashkent State Medical University Faculty of General Medicine No.1, Student of Group 119 Tashkent, Uzbekistan Author
  • Fazliddin Arzikulov Assistant of the Department of Biomedical Engineering, Informatics, and Biophysics at Tashkent State Medical University Author

Keywords:

Artificial intelligence, hospital infections, nosocomial infection, epidemiological surveillance, monitoring system, predictive model, data analysis, risk assessment, sterilization control, clinical decision-making.

Abstract

This thesis analyzes the factors influencing the spread of hospital infections (nosocomial infections) and the application of artificial intelligence (AI) technologies in their prevention. The study examines the possibilities of early detection of infectious risk zones through AI-based monitoring systems, digital tracking of patient and medical staff movement, real-time processing of epidemiological data, and the development of predictive models. Proposals have been developed to improve infection process forecasting, strengthen control in sterilization procedures, and enhance the effectiveness of clinical decision-making using AI technologies. The research results are aimed at improving hospital hygiene quality, reducing the spread of infections, and creating a safe environment in medical institutions.

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Published

2026-01-06

Issue

Vol. 2 No. 1 (2026)

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

MONITORING THE SPREAD OF HOSPITAL INFECTIONS USING ARTIFICIAL INTELLIGENCE. (2026). Modern American Journal of Medical and Health Sciences, 2(1), 8-13. https://usajournals.org/index.php/1/article/view/1769

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