[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100576913":3},{"organization":4,"armGroups":7,"interventions":18,"overallOfficials":10,"centralContacts":24,"locations":30,"responsibleParty":116,"collaborators":10,"id":121,"slug":122,"hasResults":123,"nctId":124,"briefTitle":125,"officialTitle":126,"acronym":10,"eligibilityCriteria":127,"healthyVolunteers":128,"sex":129,"minAge":130,"maxAge":131,"enrollmentInfo":132,"targetDuration":10,"studyType":135,"phases":10,"briefSummary":136,"conditions":137,"keywords":139,"overallStatus":33,"whyStopped":10,"lastUpdateSubmitDate":143,"lastUpdatePostDateStruct":144,"startDateStruct":147,"completionDateStruct":149,"leadSponsor":151,"locationsCount":152},{"fullName":5,"class":6},"The Eye Hospital of Wenzhou Medical University","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Healthy Cohort",null,"This group consists of individuals without any diagnosed cancer. Participants in this cohort will serve as the control group for comparison to the experimental group. No interventions or treatments will be administered to this cohort, as they represent a baseline of healthy individuals.",[13],"Diagnostic Test: AI-Based Diagnostic and Prognostic Model",{"label":15,"type":10,"description":16,"interventionNames":17},"Tumor Cohort","This group consists of individuals diagnosed with cancer, including various types. Participants in this cohort will serve as the experimental group for evaluating the effectiveness of the early prediction model in identifying cancer risks and improving diagnostic accuracy.",[13],[19],{"type":20,"name":21,"description":22,"armGroupLabels":23,"otherNames":10},"DIAGNOSTIC_TEST","AI-Based Diagnostic and Prognostic Model","This intervention involves an AI system that integrates multimodal data, including patient medical history, laboratory test results, imaging data, and genetic information, to predict the risk of cancer. The system uses deep learning algorithms to provide real-time, accurate predictions, enabling early identification of cancer risks. By analyzing historical health data, the model aims to predict potential cancer developments, improving early detection and treatment outcomes.",[9,15],[25],{"name":26,"role":27,"phone":28,"phoneExt":10,"email":29},"Fei Liu, MD","CONTACT","+86 13810512704","liufei_2359@163.com",[31,49,59,69,79,93,106],{"facility":32,"status":33,"city":34,"state":35,"zip":10,"country":36,"countryCode":37,"cosmosGeoPoint":38,"geoPoint":43,"contacts":44},"Guangzhou Women and Children's Medical Center","RECRUITING","Guangzhou","Guangdong","China","CN",{"type":39,"coordinates":40},"Point",[41,42],113.25,23.11667,{"lat":42,"lon":41},[45],{"name":46,"role":27,"phone":47,"phoneExt":10,"email":48},"Bingzhou Li, MD","+86-0756-2222569","mr_jerry_99@163.com",{"facility":50,"status":33,"city":34,"state":35,"zip":10,"country":36,"countryCode":37,"cosmosGeoPoint":51,"geoPoint":53,"contacts":54},"Nanfang Hospital",{"type":39,"coordinates":52},[41,42],{"lat":42,"lon":41},[55],{"name":56,"role":27,"phone":57,"phoneExt":10,"email":58},"Zhuomin Li, MD","+86-0577-85397527","chetneyli.1001@gmail.com",{"facility":60,"status":33,"city":34,"state":35,"zip":10,"country":36,"countryCode":37,"cosmosGeoPoint":61,"geoPoint":63,"contacts":64},"Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University",{"type":39,"coordinates":62},[41,42],{"lat":42,"lon":41},[65],{"name":66,"role":27,"phone":67,"phoneExt":10,"email":68},"Yunfang Yu, MD","+86 020-81332199","yuyf9@mail.sysu.edu.cn",{"facility":70,"status":33,"city":34,"state":35,"zip":10,"country":36,"countryCode":37,"cosmosGeoPoint":71,"geoPoint":73,"contacts":74},"Sun Yat-sen University Cancer Hospital",{"type":39,"coordinates":72},[41,42],{"lat":42,"lon":41},[75],{"name":76,"role":27,"phone":77,"phoneExt":10,"email":78},"Yuxing Lu, MD","+86 13161233730","yxlu0613@gmail.com",{"facility":80,"status":33,"city":81,"state":82,"zip":10,"country":36,"countryCode":37,"cosmosGeoPoint":83,"geoPoint":87,"contacts":88},"West China Hospital","Chengdu","Sichuan",{"type":39,"coordinates":84},[85,86],104.06667,30.66667,{"lat":86,"lon":85},[89],{"name":90,"role":27,"phone":91,"phoneExt":10,"email":92},"Kai Wang, MD","+86 028-85422114","wkai@stu.pku.edu.cn",{"facility":94,"status":33,"city":95,"state":96,"zip":10,"country":36,"countryCode":37,"cosmosGeoPoint":97,"geoPoint":101,"contacts":102},"First Affiliated Hospital of Wenzhou Medical University","Wenzhou","Zhejiang",{"type":39,"coordinates":98},[99,100],120.66682,27.99942,{"lat":100,"lon":99},[103],{"name":104,"role":27,"phone":10,"phoneExt":10,"email":105},"Cheng Tang, MD","c249325687@163.com",{"facility":107,"status":33,"city":95,"state":96,"zip":10,"country":36,"countryCode":37,"cosmosGeoPoint":108,"geoPoint":110,"contacts":111},"Second Affiliated Hospital of Wenzhou Medical University",{"type":39,"coordinates":109},[99,100],{"lat":100,"lon":99},[112],{"name":113,"role":27,"phone":114,"phoneExt":10,"email":115},"Sian Liu, MD","+86-0577-88002888","liusan@mail3.sysu.edu.cn",{"type":117,"investigatorFullName":118,"investigatorTitle":119,"investigatorAffiliation":120,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","Kang Zhang","Chief Scientist","Wenzhou Medical University","100576913","ai-driven-cancer-diagnosis-and-prediction-with-ehr-100576913",false,"NCT06791473","AI-Driven Cancer Diagnosis and Prediction With EHR","AI-Based Cancer Diagnosis and Prediction Using Electronic Health Records","Inclusion Criteria:\n\n1、Patients with comprehensive electronic health records (EHRs), including medical history, laboratory test results, imaging data, and genetic data (if available).\n\n2\\. Individuals without severe cognitive impairments or conditions that would prevent them from providing informed consent or participating in the study.\n\n3\\. Parents or guardians must provide informed consent for minors, while adult participants must provide informed consent for themselves.\n\nExclusion Criteria:\n\n1. Patients with incomplete or missing key electronic health record data or insufficient follow-up data.\n2. Individuals with severe cognitive disorders or other terminal illnesses that would prevent meaningful participation.\n3. Pregnant women (although pediatric cancers are being considered, pregnant women would be excluded for safety reasons).",true,"ALL","0 Years","90 Years",{"count":133,"type":134},1000000,"ESTIMATED","OBSERVATIONAL","This is a multi-center, clinical study designed to evaluate the application and effectiveness of an AI-assisted predictive model for identifying and diagnosing cancer, leveraging multimodal health data.",[138],"Tumor",[140,141,142],"tumor","Early Disease Prediction","AI-Assisted Diagnosis","2025-07-25",{"date":145,"type":146},"2025-07-30","ACTUAL",{"date":148,"type":146},"2025-01-19",{"date":150,"type":134},"2025-10-01",{"name":5,"class":6},7]