[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100558422":3},{"organization":4,"armGroups":7,"interventions":20,"overallOfficials":30,"centralContacts":34,"locations":45,"responsibleParty":62,"collaborators":25,"id":64,"slug":65,"hasResults":66,"nctId":67,"briefTitle":68,"officialTitle":68,"acronym":69,"eligibilityCriteria":70,"healthyVolunteers":71,"sex":72,"minAge":73,"maxAge":25,"enrollmentInfo":74,"targetDuration":25,"studyType":77,"phases":78,"briefSummary":80,"conditions":81,"keywords":84,"overallStatus":48,"whyStopped":25,"lastUpdateSubmitDate":86,"lastUpdatePostDateStruct":87,"startDateStruct":90,"completionDateStruct":92,"leadSponsor":94,"locationsCount":95},{"fullName":5,"class":6},"Wuerzburg University Hospital","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Training with real images","ACTIVE_COMPARATOR","Physicians train using the Paris classification with real colon polyp images",[13],"Other: Lutetia Training Plattform - real images",{"label":15,"type":16,"description":17,"interventionNames":18},"Training with artificial images","EXPERIMENTAL","Physicians train using the Paris classification with artificial colon polyp images",[19],"Other: Lutetia Training Plattform - artifical images",[21,26],{"type":6,"name":22,"description":23,"armGroupLabels":24,"otherNames":25},"Lutetia Training Plattform - real images","Training platform Lutetia offers training the Paris classification using real images of colon polyps.",[9],null,{"type":6,"name":27,"description":28,"armGroupLabels":29,"otherNames":25},"Lutetia Training Plattform - artifical images","Training platform Lutetia offers training the Paris classification using artificial images of colon polyps.",[15],[31],{"name":32,"affiliation":5,"role":33},"Alexander Hann","PRINCIPAL_INVESTIGATOR",[35,41],{"name":36,"role":37,"phone":38,"phoneExt":39,"email":40},"Alexander Hann, MD","CONTACT","0049931201","45918","hann_a@ukw.de",{"name":42,"role":37,"phone":38,"phoneExt":43,"email":44},"Ronja Weber","40242","ronja.weber@stud-mail.uni-wuerzburg.de",[46],{"facility":47,"status":48,"city":49,"state":25,"zip":25,"country":50,"countryCode":51,"cosmosGeoPoint":52,"geoPoint":57,"contacts":58},"University hospital Würzburg","RECRUITING","Würzburg","Germany","DE",{"type":53,"coordinates":54},"Point",[55,56],9.95121,49.79391,{"lat":56,"lon":55},[59],{"name":60,"role":37,"phone":61,"phoneExt":25,"email":40},"Prof. Dr. med. Hann","+49 931 201 45918",{"type":63,"investigatorFullName":25,"investigatorTitle":25,"investigatorAffiliation":25,"oldNameTitle":25,"oldOrganization":25},"SPONSOR","100558422","training-physicians-to-differentiate-the-paris-classification-using-artificial-colon-polyp-images-100558422",false,"NCT06550908","Training Physicians to Differentiate the Paris Classification Using Artificial Colon Polyp Images","LUTETIA2","Inclusion Criteria:\n\n* Physicians with or without experience in colonoscopy",true,"ALL","18 Years",{"count":75,"type":76},70,"ESTIMATED","INTERVENTIONAL",[79],"NA","Training in endoscopy is essential for the early detection of precursors of colorectal cancer. Up to now, this training has been carried out with image collections of findings and in practice when working on patients. The investigators want to use artificial intelligence (AI) to better train doctors to recognise these precursors. By using generative AI, the investigators were able to create realistic images that comply with data protection regulations and whose content can be predefined. Parts of the image can also be regenerated so that it is possible to create different precancerous stages in the same place in the image.\n\nIn this study the investigators want to train physicians using real images or artificial images in order to compare which version helps classify polyps better.",[82,83],"Colonic Polyp","Colon Adenoma",[85],"Colonoscopy","2025-08-06",{"date":88,"type":89},"2025-08-12","ACTUAL",{"date":91,"type":89},"2025-04-15",{"date":93,"type":76},"2025-08-31",{"name":5,"class":6},1]