ENHANCING THE EFFECTIVENESS OF DIAGNOSING RECURRENT CHRONIC POLYPOSIS RHINOSINUSITIS USING ARTIFICIAL INTELLIGENCE

Rakhimjonova Gulnora Abdumajidovna, Soatov Ilyosjon Olim ugli

Authors

Rakhimjonova Gulnora Abdumajidovna, Soatov Ilyosjon Olim ugli Tashkent State Medical University

Keywords:

recurrent rhinosinusitis, polyp, artificial intelligence, neural network, CT analysis, diagnosis, biomarker, morphology.

Abstract

This scientific article analyzes the effectiveness of using artificial intelligence (AI) technologies in diagnosing recurrent chronic polyposis rhinosinusitis (RCPRS). The study examined the application of neural network-based algorithms in analyzing clinical, morphological, and computed tomography (CT) data. It has been proven that the automated model created using artificial intelligence demonstrates high sensitivity and accuracy in determining the probability of polyp recurrence. The results show that the use of AI systems increases diagnostic accuracy by 20-25% and reduces errors caused by human factors.

References

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