[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100557797":3},{"organization":4,"armGroups":7,"interventions":18,"overallOfficials":24,"centralContacts":28,"locations":10,"responsibleParty":34,"collaborators":10,"id":36,"slug":37,"hasResults":38,"nctId":39,"briefTitle":40,"officialTitle":41,"acronym":10,"eligibilityCriteria":42,"healthyVolunteers":43,"sex":44,"minAge":10,"maxAge":10,"enrollmentInfo":45,"targetDuration":48,"studyType":49,"phases":10,"briefSummary":50,"conditions":51,"keywords":55,"overallStatus":59,"whyStopped":10,"lastUpdateSubmitDate":60,"lastUpdatePostDateStruct":61,"startDateStruct":64,"completionDateStruct":66,"leadSponsor":68,"locationsCount":10},{"fullName":5,"class":6},"Xinhua Hospital, Shanghai Jiao Tong University School of Medicine","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"experts",null,"with over 20 years of experience in ANA-IIF reading",[13],"Behavioral: referring to the results of AI model output",{"label":15,"type":10,"description":16,"interventionNames":17},"junior cytopathologists","less than 5 years of academic medical experience",[13],[19],{"type":20,"name":21,"description":22,"armGroupLabels":23,"otherNames":10},"BEHAVIORAL","referring to the results of AI model output","determining the ANA pattern type with or without referring to the results of AI model output.",[9,15],[25],{"name":26,"affiliation":5,"role":27},"Guangyu Chen, PhD","STUDY_DIRECTOR",[29],{"name":30,"role":31,"phone":32,"phoneExt":10,"email":33},"Junxiang Zeng, Dr","CONTACT","+8613162232879","zengjunxiang@xinhuamed.com.cn",{"type":35,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR","100557797","realistic-in-generation-of-hep-2-cell-images-using-latent-diffusion-models-a-multi-center-visual-turing-test-100557797",false,"NCT06542783","Realistic in Generation of HEp-2 Cell Images Using Latent Diffusion Models: a Multi-center Visual Turing Test","Evaluating the Realism of ANA HEp-2 Cell Images Synthesized Using Latent Diffusion Models: A Multi-center Visual Turing Test","Inclusion Criteria:\n\n* Originating from reputable medical institutions\n* Possessing relevant certification and qualifications\n* Having over one year of experience in interpreting anti-nuclear antibody (ANA) patterns within a laboratory setting\n\nExclusion Criteria:\n\n* Lacking relevant professional certification and qualifications\n* Without experience in interpreting ANA patterns\n* Unwilling to accept the rules and informed consent of the visual Turing test",true,"ALL",{"count":46,"type":47},300,"ESTIMATED","6 Months","OBSERVATIONAL","The objective of this prospective observational study is to rigorously examine the feasibility and efficacy of utilizing latent diffusion models for data augmentation in anti-nuclear antibody (ANA) Hep-2 cell immunofluorescence images. The main question it aims to answer is:\n\nCan the application of such models potentially enhance the data quality, increase sample diversity, or improve the accuracy and efficiency of subsequent analytical processes (like disease diagnosis and classification) when utilized with ANA-related images?",[52,53,54],"Anti-nuclear Antibody","Visual Turing Tests","Artifical Intelligence",[56,57,58],"anti-nuclear antibody","latent diffusion models","Visual Turing tests","NOT_YET_RECRUITING","2024-08-02",{"date":62,"type":63},"2024-08-07","ACTUAL",{"date":65,"type":47},"2024-09",{"date":67,"type":47},"2026-06",{"name":5,"class":6}]