Early Detection of Barrett's Esophagus Through Deep Image Retrieval
NCT ID: NCT04478929
Last Updated: 2020-07-21
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
300 participants
OBSERVATIONAL
2020-08-31
2021-08-31
Brief Summary
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Detailed Description
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The data will be labelled by either researchers, or professional clinicians and prepared ready to feed into a chosen learning AI system. Through an iterative learning process, the chosen AI system will learn to discriminate between severity of Barrett's oesophagus and output optimal biopsy target.
Conditions
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Study Design
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CASE_CONTROL
PROSPECTIVE
Study Groups
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gastroscopy clinic patients
NBT gastroscopy clinic invited participants. Patients are already due to attend the clinic, and we are inviting them to share their gastroscopy data with our research study.
Gastroscopy
Routine gastroscopy
Interventions
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Gastroscopy
Routine gastroscopy
Eligibility Criteria
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Inclusion Criteria
* Attending Southmead Hospital for on OGD
* Has capacity
* Initially any indication, later patients with known Barrett's oesophagus
Exclusion Criteria
* Patients without capacity
* Urgent and emergency procedures
* Limited English
18 Years
ALL
Yes
Sponsors
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Cancer Research UK
OTHER
Leigh Taylor
OTHER
Responsible Party
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Leigh Taylor
Senior Research Officer
Locations
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NBT, Southmead Hospital
Bristol, Avon, United Kingdom
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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REDM0227_RP01
Identifier Type: -
Identifier Source: org_study_id
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