AI program predicts bacterial species from urine Gram stain specimens
Development and Evaluation of AI Program for Predicting Bacterial Species From Urine Gram Stain Specimens
This study is testing a new AI program that helps doctors quickly and accurately identify bacteria in urine samples to make diagnosing infections easier.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 15000 (estimated) |
| Sex | All |
| Sponsor | GramEye Industry-sponsored |
| Locations | 1 site (Shinjuku-Ku, Tokyo) |
| Trial ID | NCT06554145 on ClinicalTrials.gov |
What this trial studies
This research aims to develop an artificial intelligence program that can accurately identify bacterial species from images of Gram-stained urine specimens. The study will evaluate the effectiveness of this AI in improving the accuracy of bacterial identification and reducing the labor involved in the Gram staining process. By automating this aspect of microbiological analysis, the study seeks to enhance diagnostic efficiency in clinical settings.
Who should consider this trial
Good fit: Ideal candidates for this study are patients whose urine specimens are being tested for bacterial infections through Gram staining and culture.
Not a fit: Patients whose urine samples are not suitable for Gram staining or have requested suspension of use may not benefit from this study.
Why it matters
Potential benefit: If successful, this AI program could significantly improve the speed and accuracy of diagnosing bacterial infections in patients.
How similar studies have performed: While the use of AI in medical diagnostics is a growing field, this specific approach to automating Gram stain analysis is relatively novel and has not been extensively tested in prior studies.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Specimens for which urine culture and urine Gram staining tests were performed for clinical purposes Exclusion Criteria: * Samples for which suspension of use has been requested
Where this trial is running
Shinjuku-Ku, Tokyo
- Keio University Hospital — Shinjuku-Ku, Tokyo, Japan (Recruiting)
Study contacts
- Study coordinator: Tatsuya Yamada, M.D.
- Email: tatsuya.yamada@grameye.com
- Phone: 7028060149
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.