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Role of Artificial Intelligence (AI) in the diagnosis of Ulcerative Colitis (UC)

Detection and categorization of colonoscopy images of Ulcerative Colitis (UC) patients using Artificial Intelligence (AI) - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2025/01/079145
Enrollment
380
Registered
2025-01-21
Start date
Unknown
Completion date
Unknown
Last updated
2025-02-03

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: K515- Left sided colitis

Interventions

Intervention1: NIL: NIL

Sponsors

None listed

Eligibility

Inclusion criteria

Inclusion criteria: 1. Participants must be 18 years of age or older. 2. Participants of all genders are eligible. 3. Participants must have a confirmed diagnosis of Inflammatory Bowel Disease Ulcerative Colitis (IBD-UC).

Exclusion criteria

Exclusion criteria: 1. Participants who are unwilling to participate in the study. 2. Patients who do not have complete clinical data.

Design outcomes

Primary

MeasureTime frame
1. Highly Accurate and Standardized Diagnostic Model: Development of a reliable AI model for diagnosing UC from colonoscopy or sigmoidoscopy images, supported by standardized imaging protocols to enhance diagnostic precision and consistency. 2. Improved Clinical Efficiency and Patient Outcomes: Automation of UC diagnosis for faster, consistent assessments, leading to timely interventions, better disease management, and improved long-term outcomes for patients.Timepoint: 18-24 months

Secondary

MeasureTime frame
1. Integration with Clinical Data and Cost-Effectiveness: Integration of imaging data with clinical inputs (e.g., lab results, history) to enhance diagnostic accuracy while reducing unnecessary procedures and costs, making UC care more accessible and affordable. 2. Advancing Medical Innovation and Education: Contribution to medical innovation by expanding AI s role in gastroenterology, coupled with real-time feedback tools for training medical students and clinicians in UC diagnostics.Timepoint: 24-36 months

Countries

India

Contacts

Public ContactDr Shiran Shetty

Kasturba Medical College, MAHE, Manipal

drshiran@gmail.com8861920517

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026