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Deep learning research on idiopathic urology phenomena

Deep learning research on idiopathic urology phenomena

Principal Investigator: Mr Robert Arbanas
Approved Research ID: 58180
Approval date: March 9th 2020

Lay summary

The goal of the research is to better understand risks and causes leading to formation of kidney stones. Although many risk factors are already known, for example low fluid intake, or set of medical conditions including genetic determinants, we still don't fully understand why large percentage of the most common kidney stones form.

By applying modern machine learning ("artificial intelligence") algorithms on available patient data including basic diagnostics, sociodemographic and lifestyle data our project will try to present kidney stones formation prediction model.

Our goal is to develop information models and put the prediction information early in front of prospective patient and help avoid painful urology procedures related to kidney stones.