[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100450000":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":10,"centralContacts":10,"locations":19,"responsibleParty":40,"collaborators":10,"id":44,"slug":45,"hasResults":46,"nctId":47,"briefTitle":48,"officialTitle":49,"acronym":10,"eligibilityCriteria":50,"healthyVolunteers":46,"sex":51,"minAge":52,"maxAge":10,"enrollmentInfo":53,"targetDuration":10,"studyType":56,"phases":10,"briefSummary":57,"conditions":58,"keywords":60,"overallStatus":22,"whyStopped":10,"lastUpdateSubmitDate":63,"lastUpdatePostDateStruct":64,"startDateStruct":67,"completionDateStruct":69,"leadSponsor":71,"locationsCount":72},{"fullName":5,"class":6},"Cedars-Sinai Medical Center","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"Artificial Intelligence Screening for Cardiac Amyloidosis",null,"An artificial intelligence algorithm will produce a probability of cardiac amyloidosis that will trigger referral to specialty clinic for further evaluation.",[13],"Other: EchoNet-LVH screening for cardiac amyloidosis",[15],{"type":6,"name":16,"description":17,"armGroupLabels":18,"otherNames":10},"EchoNet-LVH screening for cardiac amyloidosis","An AI algorithm identifies LVH, low voltage, and high suspicion for cardiac amyloidosis. The intervention is the suspicion score. Patients with high suspicion score will be referred to specialty clinic for standard of care evaluation, screening, and treatment as determined by physicians.",[9],[20],{"facility":21,"status":22,"city":23,"state":24,"zip":25,"country":26,"countryCode":27,"cosmosGeoPoint":28,"geoPoint":33,"contacts":34},"Cedars-Sinai Medical Centre (Los Angeles)","RECRUITING","Los Angeles","California","90048","United States","US",{"type":29,"coordinates":30},"Point",[31,32],-118.24368,34.05223,{"lat":32,"lon":31},[35],{"name":36,"role":37,"phone":38,"phoneExt":10,"email":39},"Lily Stern, MD","CONTACT","310-248-8300","lily.stern@cshs.org",{"type":41,"investigatorFullName":42,"investigatorTitle":43,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","Lily Stern","Staff Physician","100450000","artificial-intelligence-guided-echocardiographic-screening-of-rare-diseases-echonet-screening-100450000",false,"NCT05139797","Artificial Intelligence Guided Echocardiographic Screening of Rare Diseases (EchoNet-Screening)","Artificial Intelligence Guided Echocardiographic Screening of Rare Diseases","Inclusion Criteria:\n\n* Patients who have a high suspicion for cardiac amyloidosis by AI algorithm\n\nExclusion Criteria:\n\n* Patients who decline to be seen at specialty clinic\n* Patients who have passed away","ALL","18 Years",{"count":54,"type":55},300,"ESTIMATED","OBSERVATIONAL","Despite rapidly advancing developments in targeted therapeutics and genetic sequencing, persistent limits in the accuracy and throughput of clinical phenotyping has led to a widening gap between the potential and the actual benefits realized by precision medicine.\n\nRecent advances in machine learning and image processing techniques have shown that machine learning models can identify features unrecognized by human experts and more precisely\u002Faccurately assess common measurements made in clinical practice.\n\nThe investigators have developed an algorithm, termed EchoNet-LVH, to identify cardiac hypertrophy and identify patients who would benefit from additional screening for cardiac amyloidosis and will prospectively evaluate its accuracy in identifying patients whom would benefit from additional screening for cardiac amyloidosis.",[59],"Cardiac Amyloidosis",[61,62],"Echocardiogram","Artificial Intelligence","2025-06-24",{"date":65,"type":66},"2025-06-27","ACTUAL",{"date":68,"type":66},"2021-11-18",{"date":70,"type":55},"2027-06-01",{"name":5,"class":6},1]