[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100556679":3},{"organization":4,"armGroups":7,"interventions":25,"overallOfficials":31,"centralContacts":35,"locations":10,"responsibleParty":41,"collaborators":43,"id":55,"slug":56,"hasResults":57,"nctId":58,"briefTitle":59,"officialTitle":60,"acronym":10,"eligibilityCriteria":61,"healthyVolunteers":62,"sex":63,"minAge":10,"maxAge":10,"enrollmentInfo":64,"targetDuration":10,"studyType":67,"phases":10,"briefSummary":68,"conditions":69,"keywords":10,"overallStatus":72,"whyStopped":10,"lastUpdateSubmitDate":73,"lastUpdatePostDateStruct":74,"startDateStruct":77,"completionDateStruct":78,"leadSponsor":80,"locationsCount":10},{"fullName":5,"class":6},"Zhejiang Provincial People's Hospital","OTHER",[8,12,17,21],{"label":9,"type":10,"description":11,"interventionNames":10},"Training cohort",null,"Training cohort is used to training artificial model based on multimodel ultrasound images or videos.",{"label":13,"type":10,"description":14,"interventionNames":15},"Validation cohort","Validation cohort is used to validate artificial model.",[16],"Diagnostic Test: Artificial intelligence model",{"label":18,"type":10,"description":19,"interventionNames":20},"Internal test cohort","Internal test cohort is used to internally test artificial model.",[16],{"label":22,"type":10,"description":23,"interventionNames":24},"External test cohort","External test cohort is used to internally test artificial model.",[16],[26],{"type":27,"name":28,"description":29,"armGroupLabels":30,"otherNames":10},"DIAGNOSTIC_TEST","Artificial intelligence model","Using the artificial intelligence model to diagnosis benign, borderline, and malignant ovarian masses.",[22,18,13],[32],{"name":33,"affiliation":5,"role":34},"Litao Sun, Professor","STUDY_CHAIR",[36],{"name":37,"role":38,"phone":39,"phoneExt":10,"email":40},"Yingnan Wu, Doctor","CONTACT","0086 19883106164","litaosun1971@sina.com",{"type":42,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR",[44,46,49,51,53],{"name":45,"class":6},"The Second Affiliated Hospital of Harbin Medical University",{"name":47,"class":48},"Sichuan provincial maternity and child health care hospital","UNKNOWN",{"name":50,"class":6},"The Affiliated Hospital of Qingdao University",{"name":52,"class":48},"Aksu First People's Hospital",{"name":54,"class":6},"Women's Hospital School Of Medicine Zhejiang University","100556679","research-and-application-of-ultrasonic-intelligent-diagnosis-system-for-ovarian-mass-100556679",false,"NCT06528236","Research and Application of Ultrasonic Intelligent Diagnosis System for Ovarian Mass","Research on Automatic Detection of Ovarian Mass and Intelligent Auxiliary Diagnosis System Based on Multimodal Ultrasound Images","Inclusion Criteria:\n\n1. During gynecological ultrasound examination, at least one patient with persistent ovarian tumor was found.\n2. The patient underwent surgical treatment and the histopathological results.\n\nExclusion Criteria:\n\n1. Histopathological analysis confirms non-ovarian tumor;\n2. Histopathological results are inconclusive;\n3. Issues with image quality: the ovarian mass is incomplete and does not show some surrounding tissues (but the mass is too large to exclude completely); the images are overly blurry, making it difficult to determine the characteristics of the ovarian mass (possible reasons include hardware quality issues with the ultrasound machine, motion blur, focusing problems, presence of intestinal gas in the patient); gain settings make it difficult to judge the characteristics of the ovarian mass (such as low contrast, excessively dark images, or saturation); the presence of artifacts affects the assessment of ultrasound characteristics of the ovarian mass and should be excluded.",true,"FEMALE",{"count":65,"type":66},100000,"ESTIMATED","OBSERVATIONAL","Research on automatic detection of ovarian mass and intelligent auxiliary diagnosis system based on multimodal ultrasound images.",[70,71],"Ovarian Neoplasms","Adnexal Mass","NOT_YET_RECRUITING","2024-07-25",{"date":75,"type":76},"2024-07-30","ACTUAL",{"date":75,"type":66},{"date":79,"type":66},"2029-07-30",{"name":5,"class":6}]