[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100576915":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":10,"centralContacts":12,"locations":18,"responsibleParty":94,"collaborators":10,"id":99,"slug":100,"hasResults":101,"nctId":102,"briefTitle":103,"officialTitle":104,"acronym":10,"eligibilityCriteria":105,"healthyVolunteers":106,"sex":107,"minAge":10,"maxAge":10,"enrollmentInfo":108,"targetDuration":10,"studyType":111,"phases":10,"briefSummary":112,"conditions":113,"keywords":115,"overallStatus":21,"whyStopped":10,"lastUpdateSubmitDate":117,"lastUpdatePostDateStruct":118,"startDateStruct":121,"completionDateStruct":123,"leadSponsor":125,"locationsCount":126},{"fullName":5,"class":6},"The Eye Hospital of Wenzhou Medical University","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":10},"AI-Assisted Disease Prediction Using EHR and Imaging Data",null,"This cohort consists of patients whose historical health data, including electronic health records (EHR) and multimodal imaging data (e.g., X-rays, MRIs, CT scans, ultrasounds), will be analyzed by an AI agent. The AI system will assist in diagnosing and predicting diseases by processing and integrating these diverse data sources. The primary focus is to evaluate the ability of the AI agent to identify patterns and predict disease progression with high accuracy. Participants will not be required to take any additional actions beyond providing their medical history and imaging data. The aim is to assess how well the AI system can support clinical decision-making and improve diagnostic outcomes based on the provided data.",[13],{"name":14,"role":15,"phone":16,"phoneExt":10,"email":17},"Fei Liu, MD","CONTACT","+86 13810512704","liufei_2359@163.com",[19,37,47,57,71,84],{"facility":20,"status":21,"city":22,"state":23,"zip":10,"country":24,"countryCode":25,"cosmosGeoPoint":26,"geoPoint":31,"contacts":32},"Nanfang Hospital","RECRUITING","Guangzhou","Guangdong","China","CN",{"type":27,"coordinates":28},"Point",[29,30],113.25,23.11667,{"lat":30,"lon":29},[33],{"name":34,"role":15,"phone":35,"phoneExt":10,"email":36},"Zhuomin Li","+86-0577-85397527","chetneyli.1001@gmail.com",{"facility":38,"status":21,"city":22,"state":23,"zip":10,"country":24,"countryCode":25,"cosmosGeoPoint":39,"geoPoint":41,"contacts":42},"Sun Yat-Sen Memorial Hospital",{"type":27,"coordinates":40},[29,30],{"lat":30,"lon":29},[43],{"name":44,"role":15,"phone":45,"phoneExt":10,"email":46},"Yunfang Yu","+86 020-81332199","yuyf9@mail.sysu.edu.cn",{"facility":48,"status":21,"city":22,"state":23,"zip":10,"country":24,"countryCode":25,"cosmosGeoPoint":49,"geoPoint":51,"contacts":52},"Sun Yat-sen University Cancer Hospital",{"type":27,"coordinates":50},[29,30],{"lat":30,"lon":29},[53],{"name":54,"role":15,"phone":55,"phoneExt":10,"email":56},"Yuxing Lu","+86 13161233730","yxlu0613@gmail.com",{"facility":58,"status":21,"city":59,"state":60,"zip":10,"country":24,"countryCode":25,"cosmosGeoPoint":61,"geoPoint":65,"contacts":66},"West China Hospital","Chengdu","Sichuan",{"type":27,"coordinates":62},[63,64],104.06667,30.66667,{"lat":64,"lon":63},[67],{"name":68,"role":15,"phone":69,"phoneExt":10,"email":70},"Kai Wang","+86 028-85422114","wkai@stu.pku.edu.cn",{"facility":72,"status":21,"city":73,"state":74,"zip":10,"country":24,"countryCode":25,"cosmosGeoPoint":75,"geoPoint":79,"contacts":80},"First Affiliated Hospital of Wenzhou Medical University","Wenzhou","Zhejiang",{"type":27,"coordinates":76},[77,78],120.66682,27.99942,{"lat":78,"lon":77},[81],{"name":82,"role":15,"phone":10,"phoneExt":10,"email":83},"Cheng Tang","c249325687@163.com",{"facility":85,"status":21,"city":73,"state":74,"zip":10,"country":24,"countryCode":25,"cosmosGeoPoint":86,"geoPoint":88,"contacts":89},"Second Affiliated Hospital of Wenzhou Medical University",{"type":27,"coordinates":87},[77,78],{"lat":78,"lon":77},[90],{"name":91,"role":15,"phone":92,"phoneExt":10,"email":93},"Sian Liu","+86-0577-88002888","liusan@mail3.sysu.edu.cn",{"type":95,"investigatorFullName":96,"investigatorTitle":97,"investigatorAffiliation":98,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","Kang Zhang","Chief Scientist","Wenzhou Medical University","100576915","ai-agent-for-automated-diagnosis-and-predicting-using-ehr-and-multimodal-data-100576915",false,"NCT06791499","AI-Agent for Automated Diagnosis and Predicting Using EHR and Multimodal Data","AI-Agent Assisted Automation for Diagnosing and Predicting Patients Using Electronic Health Records and Multimodal Data","Inclusion Criteria:\n\n1. Participants must have comprehensive electronic health records (EHR) available, including demographic information, medical history, and laboratory results.\n2. Participants must have available multimodal imaging data (e.g., X-rays, CT scans, MRIs, ultrasounds) relevant to their health condition.\n3. Participants must have a confirmed diagnosis of one or more diseases or health conditions based on clinical records or imaging data.\n4. Patients must provide consent for the use of their historical health data for research purposes.\n\nExclusion Criteria:\n\n1. Participants with ambiguous or unverifiable diagnoses that cannot be accurately categorized.\n2. Duplicate or redundant patient data (e.g., repeated records of the same patient without clear differentiation).",true,"ALL",{"count":109,"type":110},2000000,"ESTIMATED","OBSERVATIONAL","The goal of this clinical study is to evaluate the effectiveness of an AI agent in diagnosing and predicting diseases using electronic health records (EHR) and multimodal imaging data. The AI agent leverages advanced machine learning algorithms to process and analyze diverse health data sources, aiming to assist healthcare providers in making more accurate diagnoses and predictions.",[114],"AI Agent",[116],"AI agent","2025-04-16",{"date":119,"type":120},"2025-04-17","ACTUAL",{"date":122,"type":120},"2023-07-01",{"date":124,"type":110},"2025-07",{"name":5,"class":6},6]