PREDICTION OF BLOOD LOSS DURING OPERATIONS USING AI

Authors

  • Begmurodov Nodirbek Mo’min o’g’li 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, machine learning, surgery, bleeding prediction, medical data analysis, clinical decision support.

Abstract

This study addresses the issue of predicting bleeding during surgical operations using artificial intelligence (AI) technologies. Based on modern machine learning and deep learning algorithms, patient clinical parameters, laboratory tests, imaging diagnostic data, and factors related to the surgical process are analyzed. AI-based prediction models allow surgeons to identify high-risk cases in advance, minimize blood loss, and increase surgical safety. The results of the study show that the use of artificial intelligence can help to more accurately assess the risk of intraoperative bleeding, support clinical decision-making, and reduce the number of complications.

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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

PREDICTION OF BLOOD LOSS DURING OPERATIONS USING AI. (2026). Eureka Journal of Health Sciences & Medical Innovation, 2(1), 45-52. https://eurekaoa.com/index.php/5/article/view/127

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