[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100631174":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":10,"centralContacts":26,"locations":32,"responsibleParty":79,"collaborators":10,"id":81,"slug":10,"hasResults":82,"nctId":83,"briefTitle":84,"officialTitle":85,"acronym":10,"eligibilityCriteria":86,"healthyVolunteers":87,"sex":88,"minAge":10,"maxAge":10,"enrollmentInfo":89,"targetDuration":92,"studyType":93,"phases":10,"briefSummary":94,"conditions":95,"keywords":97,"overallStatus":102,"whyStopped":10,"lastUpdateSubmitDate":103,"lastUpdatePostDateStruct":104,"startDateStruct":107,"completionDateStruct":109,"leadSponsor":111,"locationsCount":112},{"fullName":5,"class":6},"Union Hospital, Tongji Medical College, Huazhong University of Science and Technology","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Radiologist diagnostic group",null,"After the patient undergoes an X-ray examination, a radiologist generates the report and makes the diagnosis.",[13],"Diagnostic Test: Radiologist diagnostic group",{"label":15,"type":10,"description":16,"interventionNames":17},"AI-assisted radiologist diagnostic group","After the patient undergoes an X-ray examination, an AI-assisted radiologist generates the report and makes the diagnosis.",[18],"Diagnostic Test: AI-assisted radiologist diagnostic group",[20,24],{"type":21,"name":15,"description":22,"armGroupLabels":23,"otherNames":10},"DIAGNOSTIC_TEST","Based on the previously developed X-ray image diagnosis and report generation model, radiologists are assisted in interpreting X-ray images and generating reports.",[15],{"type":21,"name":9,"description":11,"armGroupLabels":25,"otherNames":10},[9],[27],{"name":28,"role":29,"phone":30,"phoneExt":10,"email":31},"Huangxuan Zhao, PhD","CONTACT","18971676985","zhao_huangxuan@sina.com",[33,50,58,66],{"facility":34,"status":10,"city":35,"state":36,"zip":37,"country":38,"cosmosGeoPoint":39,"geoPoint":44,"contacts":45},"Wuhan Union Hospital","Wuhan","Hubei","430022","China",{"type":40,"coordinates":41},"Point",[42,43],114.26667,30.58333,{"lat":43,"lon":42},[46],{"name":47,"role":29,"phone":48,"phoneExt":10,"email":49},"Lei Chen, MD","15971480677","chan0812@126.com",{"facility":51,"status":10,"city":35,"state":36,"zip":37,"country":38,"cosmosGeoPoint":52,"geoPoint":54,"contacts":55},"Wuhan Union Jinyin Lake Hospital",{"type":40,"coordinates":53},[42,43],{"lat":43,"lon":42},[56],{"name":57,"role":29,"phone":48,"phoneExt":10,"email":49},"Lei Chen",{"facility":59,"status":10,"city":35,"state":36,"zip":37,"country":38,"cosmosGeoPoint":60,"geoPoint":62,"contacts":63},"Wuhan Union West Hospital",{"type":40,"coordinates":61},[42,43],{"lat":43,"lon":42},[64],{"name":65,"role":29,"phone":30,"phoneExt":10,"email":31},"Huangxuan Zhao",{"facility":67,"status":10,"city":68,"state":10,"zip":10,"country":38,"cosmosGeoPoint":69,"geoPoint":73,"contacts":74},"The First Affiliated Hospital of Zhengzhou University","Zhengzhou",{"type":40,"coordinates":70},[71,72],113.64861,34.75778,{"lat":72,"lon":71},[75],{"name":76,"role":29,"phone":77,"phoneExt":10,"email":78},"Huangxuan Duan","13209867189","xuhuaduan2023@126.com",{"type":80,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR","100631174",false,"NCT07497243","X-ray Assisted Diagnostic System","Construction and Clinical Application of an X-ray AI-Aided Diagnosis System: A Randomized Controlled Trial","Inclusion Criteria:\n\n* Clinically suspected thoracic diseases (such as pneumonia, tuberculosis, or lung cancer) requiring X-ray diagnosis；\n* Patients providing written informed consent for research data use；\n* Complete clinical records (including chief complaints, medical history, and laboratory test results)\n\nExclusion Criteria:\n\n* Substandard X-ray image quality (including severe motion artifacts, over-\u002Funderexposure, or missing anatomical structures)\n* Pregnant or lactating women",true,"ALL",{"count":90,"type":91},16000,"ESTIMATED","4 Weeks","OBSERVATIONAL","X-ray examination is one of the most commonly used imaging modalities, especially chest X-ray, which is routinely performed for hospitalized patients. However, due to the low density resolution of X-ray images, radiologists' ability to diagnose diseases-particularly small lesions-is often affected. Studies have shown that the diagnostic accuracy of radiologists using chest X-rays is only around 70%, which does not meet clinical demands.\n\nBased on this, we developed an artificial intelligence model to assist radiologists in interpreting X-ray images and generating reports, with the aim of improving diagnostic accuracy and reducing interpretation time.",[96],"Chest X-ray for Clinical Evaluation",[98,99,100,101],"X-Ray","AI","Chest diseases","Accuracy","NOT_YET_RECRUITING","2026-03-22",{"date":105,"type":106},"2026-03-27","ACTUAL",{"date":108,"type":91},"2026-05-01",{"date":110,"type":91},"2026-11-30",{"name":5,"class":6},4]