se of phone based application to track patients with stents( tubes placed between kidney and urinary bladder)after surgery for stones in kidney , so asto prevent retained stents and related problems.
Not Applicable
- Conditions
- Health Condition 1: N00-N99- Diseases of the genitourinary system
- Registration Number
- CTRI/2020/09/027665
- Lead Sponsor
- Kasturba Medical College
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- ot Yet Recruiting
- Sex
- Not specified
- Target Recruitment
- 0
Inclusion Criteria
Any patient having kidney and ureteric stone and undergoing endoscopic procedure.
Exclusion Criteria
Patient not willing to participate in the study, Pregnancy (cannot undergo NCCT)
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Accuracy of deep learning and artificial intelligence techniques in identifying the renal stones. <br/ ><br>- Accuracy of Deep learning and Artificial Intelligence techniques in identifying the stone composition as compared to stone analysis <br/ ><br>Timepoint: data is collected after the patinet undergoes CT scan
- Secondary Outcome Measures
Name Time Method The decrease in recurrence rate of stones in patients after starting treatment based on stone composition detected through deep learning and artificial intelligence.Timepoint: After the initial treatment, during follow up