{
  "api_version": "1",
  "request": {
    "url": "https://clinicaltrialsfind.com/api/v1/search.json?intervention=AI-POCUS",
    "query": {
      "intervention": "AI-POCUS"
    },
    "page_size": 10
  },
  "pagination": {
    "page": 1,
    "page_size": 10,
    "total_count": 9,
    "total_pages": 1,
    "next_page_url": null,
    "previous_page_url": null
  },
  "source": "remote",
  "last_synced_at": "2026-09-04T09:19:13.681Z",
  "attribution": "Data derived from public ClinicalTrials.gov records. The official record at https://clinicaltrials.gov/ remains the source of truth for current availability, contacts, and full study details.",
  "notes": [
    "This endpoint exposes only public summary fields — no participant contact emails, phone numbers, or scraped investigator contact details.",
    "For contact information and full protocol detail, follow each trial's `official_url` to the ClinicalTrials.gov record.",
    "This API is a navigational aid. It does not provide medical advice, eligibility determinations, or compensation guarantees."
  ],
  "trials": [
    {
      "nct_id": "NCT07800962",
      "title": "Federated Learning for Point-of-Care Cardiac Ultrasound",
      "overall_status": "ENROLLING_BY_INVITATION",
      "study_type": "OBSERVATIONAL",
      "phases": [],
      "conditions": [
        "Ventricular Dysfunction, Left",
        "Ventricular Function, Left",
        "Echocardiography",
        "Ultrasonography",
        "Point-of-Care Systems",
        "Heart Function Tests",
        "Stroke Volume",
        "Federated Learning",
        "Machine Learning",
        "Artificial Intelligence (AI)",
        "Deep Learning",
        "Neural Networks, Computer",
        "Image Interpretation, Computer-Assisted",
        "Diagnosis, Computer-Assisted",
        "Sensitivity and Specificity",
        "ROC Curve"
      ],
      "interventions": [
        {
          "name": "Focused Cardiac Point-of-Care Ultrasonography",
          "type": "DIAGNOSTIC_TEST"
        },
        {
          "name": "FL-POCUS Federated Machine-Learning Analysis System",
          "type": "DEVICE"
        }
      ],
      "intervention_types": [
        "DIAGNOSTIC_TEST",
        "DEVICE"
      ],
      "sponsor": "Truway Health, Inc.",
      "sponsor_class": "INDUSTRY",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "18 Years and older"
      },
      "enrollment_count": 3000,
      "start_date": "2026-08-31",
      "completion_date": "2037-09-30",
      "has_results": false,
      "last_update_posted_date": "2026-09-02",
      "last_synced_at": "2026-09-04T09:19:13.681Z",
      "location_count": 1,
      "location_summary": "New York, New York",
      "locations": [
        {
          "city": "New York",
          "state": "New York"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07800962"
    },
    {
      "nct_id": "NCT07503158",
      "title": "Prospective Evaluation of Cardiac Point-of-Care Ultrasound (POCUS) Performed by PEM Fellows and Artificial Intelligence on Children With Pre-existing Cardiac Conditions.",
      "overall_status": "NOT_YET_RECRUITING",
      "study_type": "OBSERVATIONAL",
      "phases": [],
      "conditions": [
        "Cardiac Anomalies"
      ],
      "interventions": [
        {
          "name": "AI Pocus_Cardiac",
          "type": "DIAGNOSTIC_TEST"
        }
      ],
      "intervention_types": [
        "DIAGNOSTIC_TEST"
      ],
      "sponsor": "Nicklaus Children's Hospital f/k/a Miami Children's Hospital",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "1 Month",
        "maximum_age": "21 Years",
        "sex": "ALL",
        "summary": "1 Month to 21 Years"
      },
      "enrollment_count": 200,
      "start_date": "2026-03-30",
      "completion_date": "2028-03-30",
      "has_results": false,
      "last_update_posted_date": "2026-04-08",
      "last_synced_at": "2026-09-04T09:19:13.681Z",
      "location_count": 1,
      "location_summary": "Miami, Florida",
      "locations": [
        {
          "city": "Miami",
          "state": "Florida"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07503158"
    },
    {
      "nct_id": "NCT07756398",
      "title": "Importance of Point-of-Care Ultrasound for Early Detection of Valvular and Cardiac Diseases (IMPROVE)",
      "overall_status": "NOT_YET_RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Valvular Heart Disease Patients",
        "Aortic Stenosis",
        "Mitral Regurgitation",
        "Left Ventricular Diastolic Dysfunction"
      ],
      "interventions": [
        {
          "name": "Kosmos Torso-One AI-guided Point-of-Care Ultrasound (EchoNous, Inc.)",
          "type": "DEVICE"
        }
      ],
      "intervention_types": [
        "DEVICE"
      ],
      "sponsor": "University of Texas Southwestern Medical Center",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "65 Years",
        "maximum_age": "85 Years",
        "sex": "ALL",
        "summary": "65 Years to 85 Years"
      },
      "enrollment_count": 1088,
      "start_date": "2026-08-01",
      "completion_date": "2028-12-01",
      "has_results": false,
      "last_update_posted_date": "2026-08-17",
      "last_synced_at": "2026-09-04T09:19:13.681Z",
      "location_count": 2,
      "location_summary": "Dallas, Texas",
      "locations": [
        {
          "city": "Dallas",
          "state": "Texas"
        },
        {
          "city": "Dallas",
          "state": "Texas"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07756398"
    },
    {
      "nct_id": "NCT07062848",
      "title": "An Observational Study Using Artificial Intelligence (AI) Algorithms on Electrocardiography (ECG), Point-of-care Ultrasound (POCUS), and Transthoracic Echocardiophy (TTE) to Estimate the Under-diagnosis of Transthyretin Amyloid Cardiomyopathy (ATTR-CM) Across a Diverse Range of US Health Systems.",
      "overall_status": "ACTIVE_NOT_RECRUITING",
      "study_type": "OBSERVATIONAL",
      "phases": [],
      "conditions": [
        "Transthyretin (TTR) Amyloid Cardiomyopathy"
      ],
      "interventions": [
        {
          "name": "AI Toolkit for ATTR-CM Diagnosis",
          "type": "DIAGNOSTIC_TEST"
        }
      ],
      "intervention_types": [
        "DIAGNOSTIC_TEST"
      ],
      "sponsor": "Yale University",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "50 Years",
        "maximum_age": "95 Years",
        "sex": "ALL",
        "summary": "50 Years to 95 Years"
      },
      "enrollment_count": 1500000,
      "start_date": "2025-01-24",
      "completion_date": "2027-01",
      "has_results": false,
      "last_update_posted_date": "2026-07-29",
      "last_synced_at": "2026-09-04T09:19:13.681Z",
      "location_count": 12,
      "location_summary": "San Francisco, California • New Haven, Connecticut • Chicago, Illinois + 9 more",
      "locations": [
        {
          "city": "San Francisco",
          "state": "California"
        },
        {
          "city": "New Haven",
          "state": "Connecticut"
        },
        {
          "city": "Chicago",
          "state": "Illinois"
        },
        {
          "city": "Detroit",
          "state": "Michigan"
        },
        {
          "city": "New York",
          "state": "New York"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07062848"
    },
    {
      "nct_id": "NCT06749145",
      "title": "Deep Learning Enhanced Detection of Aortic Stenosis - The DETECT-AS-Diagnostic Study",
      "overall_status": "ENROLLING_BY_INVITATION",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Aortic Stenosis"
      ],
      "interventions": [
        {
          "name": "Portable 1-lead electrocardiogram",
          "type": "DIAGNOSTIC_TEST"
        },
        {
          "name": "Point-of-care ultrasound",
          "type": "DIAGNOSTIC_TEST"
        },
        {
          "name": "AI-ECG risk algorithm",
          "type": "OTHER"
        },
        {
          "name": "AI-POCUS",
          "type": "OTHER"
        }
      ],
      "intervention_types": [
        "DIAGNOSTIC_TEST",
        "OTHER"
      ],
      "sponsor": "Yale University",
      "sponsor_class": "OTHER",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": "70 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "70 Years and older"
      },
      "enrollment_count": 410,
      "start_date": "2025-09-16",
      "completion_date": "2028-08-31",
      "has_results": false,
      "last_update_posted_date": "2025-11-26",
      "last_synced_at": "2026-09-04T09:19:13.681Z",
      "location_count": 3,
      "location_summary": "New Haven, Connecticut • New York, New York • Houston, Texas",
      "locations": [
        {
          "city": "New Haven",
          "state": "Connecticut"
        },
        {
          "city": "New York",
          "state": "New York"
        },
        {
          "city": "Houston",
          "state": "Texas"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT06749145"
    },
    {
      "nct_id": "NCT06548373",
      "title": "Assessment of Diagnostic Adequacy of AI-assisted Point-of-Care Echocardiography Among Anesthesiology Trainees",
      "overall_status": "ACTIVE_NOT_RECRUITING",
      "study_type": "OBSERVATIONAL",
      "phases": [],
      "conditions": [
        "Anesthesia"
      ],
      "interventions": [
        {
          "name": "Artificial Intelligence-assisted Point-of-Care Echocardiography",
          "type": "DIAGNOSTIC_TEST"
        }
      ],
      "intervention_types": [
        "DIAGNOSTIC_TEST"
      ],
      "sponsor": "Loma Linda University",
      "sponsor_class": "OTHER",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": "65 Years",
        "sex": "ALL",
        "summary": "18 Years to 65 Years"
      },
      "enrollment_count": 16,
      "start_date": "2024-08-13",
      "completion_date": "2027-12",
      "has_results": false,
      "last_update_posted_date": "2026-06-05",
      "last_synced_at": "2026-09-04T09:19:13.681Z",
      "location_count": 1,
      "location_summary": "Loma Linda, California",
      "locations": [
        {
          "city": "Loma Linda",
          "state": "California"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT06548373"
    },
    {
      "nct_id": "NCT05144633",
      "title": "Blue Protocol and Eko Artificial Intelligence Are Best (BEA-BEST)",
      "overall_status": "UNKNOWN",
      "study_type": "OBSERVATIONAL",
      "phases": [],
      "conditions": [
        "Acute Respiratory Failure"
      ],
      "interventions": [
        {
          "name": "Auscultation",
          "type": "DEVICE"
        }
      ],
      "intervention_types": [
        "DEVICE"
      ],
      "sponsor": "University of Louisville",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": "100 Years",
        "sex": "ALL",
        "summary": "18 Years to 100 Years"
      },
      "enrollment_count": 100,
      "start_date": "2021-09-09",
      "completion_date": "2025-04-30",
      "has_results": false,
      "last_update_posted_date": "2025-01-20",
      "last_synced_at": "2026-09-04T09:19:13.681Z",
      "location_count": 1,
      "location_summary": "Louisville, Kentucky",
      "locations": [
        {
          "city": "Louisville",
          "state": "Kentucky"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT05144633"
    },
    {
      "nct_id": "NCT06580158",
      "title": "AI in Outpatient Practice for Diagnosing Aortic Stenosis and Diastolic Dysfunction",
      "overall_status": "RECRUITING",
      "study_type": "OBSERVATIONAL",
      "phases": [],
      "conditions": [
        "Aortic Stenosis",
        "Diastolic Dysfunction"
      ],
      "interventions": [
        {
          "name": "AI-ECG Dashboard",
          "type": "DEVICE"
        },
        {
          "name": "Point of care ultrasound (POCUS)",
          "type": "DIAGNOSTIC_TEST"
        }
      ],
      "intervention_types": [
        "DEVICE",
        "DIAGNOSTIC_TEST"
      ],
      "sponsor": "Mayo Clinic",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "60 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "60 Years and older"
      },
      "enrollment_count": 2000,
      "start_date": "2024-11-08",
      "completion_date": "2027-03",
      "has_results": false,
      "last_update_posted_date": "2026-03-04",
      "last_synced_at": "2026-09-04T09:19:13.681Z",
      "location_count": 1,
      "location_summary": "Rochester, Minnesota",
      "locations": [
        {
          "city": "Rochester",
          "state": "Minnesota"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT06580158"
    },
    {
      "nct_id": "NCT07535294",
      "title": "Assess Patient Readiness for Pelvic Ultrasound With the Use of Artificial Intelligence",
      "overall_status": "COMPLETED",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Abdominal Pain",
        "Pelvic Pain"
      ],
      "interventions": [
        {
          "name": "Experimental AI POCUS",
          "type": "OTHER"
        },
        {
          "name": "Standard of Care Ultrasound",
          "type": "DIAGNOSTIC_TEST"
        }
      ],
      "intervention_types": [
        "OTHER",
        "DIAGNOSTIC_TEST"
      ],
      "sponsor": "Nicklaus Children's Hospital f/k/a Miami Children's Hospital",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "8 Years",
        "maximum_age": "21 Years",
        "sex": "FEMALE",
        "summary": "8 Years to 21 Years · Female only"
      },
      "enrollment_count": 520,
      "start_date": "2024-08-14",
      "completion_date": "2026-02-11",
      "has_results": false,
      "last_update_posted_date": "2026-04-24",
      "last_synced_at": "2026-09-04T09:19:13.681Z",
      "location_count": 1,
      "location_summary": "Miami, Florida",
      "locations": [
        {
          "city": "Miami",
          "state": "Florida"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07535294"
    }
  ]
}