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THE ROLE OF ALGORITHMS IN DECISION MAKING IN PRIMARY HEALTHCARE SYSTEMS

Authors

  • Berdimbetov Timur Tileubergenovich

    Nukus branch of Tashkent University of Information Technology, PhD
    Author
  • Xo‘jayev Otabek Kadambayevich

    Urgench branch of Tashkent University of Information Technology, PhD
    Author
  • Musaeva Mukhtasar Zayirjan qizi

    Master of Nukus branch of Tashkent University of Information Technology
    Author

Keywords:

Primary healthcare system, decision making, algorithms, artificial intelligence, medical diagnosis, personalized treatment, resource allocation, patient monitoring, healthcare technology, health information systems.

Abstract

This paper explores the role of algorithms in decision-making within primary healthcare systems. It examines how algorithms can improve the speed and accuracy of diagnoses, create personalized treatment plans, allocate healthcare resources efficiently, and provide continuous patient monitoring. The paper also discusses the benefits and challenges associated with the use of algorithms in healthcare, particularly regarding data quality, security, and the need for continuous updates. The findings suggest that the use of algorithms in primary healthcare systems has significant potential for improving patient outcomes and enhancing healthcare delivery.

References

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4. Le, D., & Zhang, X. (2022). "Predictive Analytics and Decision Support in Primary Care." International Journal of Medical Informatics, 139, 104234.

5. Patel, V. L., & Shortliffe, E. H. (2018). "Artificial Intelligence in Healthcare: Past, Present, and Future." Journal of the American Medical Informatics Association, 25(1), 25–37.

6. Shah, S. K., & Wood, P. (2017). "AI in Healthcare: Implications for Primary Care Decision Making." British Medical Journal (BMJ), 358, j3765.

7. Susskind, R., & Susskind, D. (2020). "The Future of the Professions: How Technology Will Transform the Work of Human Experts." Oxford University Press.

8. Wang, F., et al. (2020). "Artificial Intelligence in Health Care: A Review." Journal of the American Medical Association (JAMA), 323(6), 521–531.

9. Yang, G. et al. (2019). "Machine Learning in Healthcare: Review, Opportunities and Threats." IEEE Transactions on Biomedical Engineering, 66(8), 2182-2194.

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Published

2025-01-30