Can I read UTI - Paper Final on EtoBox?

UTI - Paper Final by ysudhanshu041 is a document available to read on EtoBox.

What is UTI - Paper Final about?

This study presents a two-stage diagnosis framework for urinary tract infections (UTIs) that combines symptom-based machine learning and deep learning image analysis. The framework utilizes a Random Forest classifier and a U-Net architecture, achieving a model recall of 0.833 and a global pixel accuracy of 99.85% on a Kaggle dataset. The results indicate that integrating clinical symptoms with microscopic image analysis can significantly enhance UTI diagnosis accuracy.

Author

ysudhanshu041

Language

EN