{
  "api_version": "1",
  "request": {
    "url": "https://clinicaltrialsfind.com/api/v1/search.json?intervention=Artificial+Intelligence+based+Intervention",
    "query": {
      "intervention": "Artificial Intelligence based Intervention"
    },
    "page_size": 10
  },
  "pagination": {
    "page": 1,
    "page_size": 10,
    "total_count": 104,
    "total_pages": 11,
    "next_page_url": "https://clinicaltrialsfind.com/api/v1/search.json?intervention=Artificial+Intelligence+based+Intervention&page=2&page_size=10",
    "previous_page_url": null
  },
  "source": "remote",
  "last_synced_at": "2026-10-22T03:03:44.976Z",
  "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": "NCT06029244",
      "title": "Eyecontrol coMmunication Platform for dEliRium manaGemEnt in Intensive Care Units (EMERGE)",
      "overall_status": "COMPLETED",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Delirium",
        "Delirium in Old Age",
        "Critical Illness",
        "Intensive Care Unit Delirium"
      ],
      "interventions": [
        {
          "name": "EyeControl-Pro",
          "type": "DEVICE"
        },
        {
          "name": "Control",
          "type": "OTHER"
        }
      ],
      "intervention_types": [
        "DEVICE",
        "OTHER"
      ],
      "sponsor": "Beth Israel Deaconess Medical Center",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "50 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "50 Years and older"
      },
      "enrollment_count": 160,
      "start_date": "2024-02-25",
      "completion_date": "2025-11-18",
      "has_results": false,
      "last_update_posted_date": "2025-12-03",
      "last_synced_at": "2026-10-22T03:03:44.976Z",
      "location_count": 1,
      "location_summary": "Boston, Massachusetts",
      "locations": [
        {
          "city": "Boston",
          "state": "Massachusetts"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT06029244"
    },
    {
      "nct_id": "NCT05423964",
      "title": "Impact of AI on Trainee ADR",
      "overall_status": "UNKNOWN",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Adenoma",
        "Adenoma Colon",
        "Colorectal Cancer"
      ],
      "interventions": [
        {
          "name": "AI use in Endoscopy Room",
          "type": "DIAGNOSTIC_TEST"
        },
        {
          "name": "Non-AI use Standard of Care endoscopy room",
          "type": "OTHER"
        }
      ],
      "intervention_types": [
        "DIAGNOSTIC_TEST",
        "OTHER"
      ],
      "sponsor": "University of Southern California",
      "sponsor_class": "OTHER",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": null,
        "maximum_age": null,
        "sex": "ALL",
        "summary": "Not listed"
      },
      "enrollment_count": 25,
      "start_date": "2023-01-01",
      "completion_date": "2025-09",
      "has_results": false,
      "last_update_posted_date": "2023-03-06",
      "last_synced_at": "2026-10-22T03:03:44.976Z",
      "location_count": 1,
      "location_summary": "Los Angeles, California",
      "locations": [
        {
          "city": "Los Angeles",
          "state": "California"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT05423964"
    },
    {
      "nct_id": "NCT07337577",
      "title": "Targeted Artificial Intelligence Language mOdel Recommendations for Heart Failure (TAILOR-HF)",
      "overall_status": "RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Heart Failure"
      ],
      "interventions": [
        {
          "name": "LLM-GDMT Clinical Decision Support Tool",
          "type": "DEVICE"
        }
      ],
      "intervention_types": [
        "DEVICE"
      ],
      "sponsor": "Brigham and Women's Hospital",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": "85 Years",
        "sex": "ALL",
        "summary": "18 Years to 85 Years"
      },
      "enrollment_count": 500,
      "start_date": "2026-08-27",
      "completion_date": "2027-12-01",
      "has_results": false,
      "last_update_posted_date": "2026-08-31",
      "last_synced_at": "2026-10-22T03:03:44.976Z",
      "location_count": 1,
      "location_summary": "Boston, Massachusetts",
      "locations": [
        {
          "city": "Boston",
          "state": "Massachusetts"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07337577"
    },
    {
      "nct_id": "NCT06240091",
      "title": "Potency and Precision Investigation",
      "overall_status": "COMPLETED",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Depression, Anxiety"
      ],
      "interventions": [
        {
          "name": "DISC-MA",
          "type": "DEVICE"
        }
      ],
      "intervention_types": [
        "DEVICE"
      ],
      "sponsor": "Woebot Health",
      "sponsor_class": "INDUSTRY",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": "75 Years",
        "sex": "ALL",
        "summary": "18 Years to 75 Years"
      },
      "enrollment_count": 203,
      "start_date": "2024-03-13",
      "completion_date": "2024-05-09",
      "has_results": true,
      "last_update_posted_date": "2025-02-19",
      "last_synced_at": "2026-10-22T03:03:44.976Z",
      "location_count": 1,
      "location_summary": "San Francisco, California",
      "locations": [
        {
          "city": "San Francisco",
          "state": "California"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT06240091"
    },
    {
      "nct_id": "NCT07534254",
      "title": "Piloting a Generative Artificial Intelligence Chatbot in a Mobile Weight Loss Program",
      "overall_status": "ACTIVE_NOT_RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Overweight and/or Obesity"
      ],
      "interventions": [
        {
          "name": "AGILE Intervention",
          "type": "BEHAVIORAL"
        },
        {
          "name": "Chatbot",
          "type": "BEHAVIORAL"
        }
      ],
      "intervention_types": [
        "BEHAVIORAL"
      ],
      "sponsor": "University of North Carolina, Chapel Hill",
      "sponsor_class": "OTHER",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": "39 Years",
        "sex": "ALL",
        "summary": "18 Years to 39 Years"
      },
      "enrollment_count": 20,
      "start_date": "2026-03-23",
      "completion_date": "2026-09-28",
      "has_results": false,
      "last_update_posted_date": "2026-06-26",
      "last_synced_at": "2026-10-22T03:03:44.976Z",
      "location_count": 1,
      "location_summary": "Chapel Hill, North Carolina",
      "locations": [
        {
          "city": "Chapel Hill",
          "state": "North Carolina"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07534254"
    },
    {
      "nct_id": "NCT07500532",
      "title": "Evaluation of the Medentum Diagnostik Platform for Pediatric ENT Conditions and Asthma",
      "overall_status": "RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Acute Otitis Media (AOM)",
        "Strep Pharyngitis",
        "Asthma Exacerbation",
        "Pediatric Asthma"
      ],
      "interventions": [
        {
          "name": "Diagnostik home-based platform: multisensor device, software application, and artificial-intelligence algorithms that predict diagnosis of AOM and strep pharyngitis",
          "type": "DEVICE"
        },
        {
          "name": "Diagnostik home-based platform: multisensor device, software application, and artificial-intelligence algorithms that predict diagnosis of wheeze/asthma exacerbation",
          "type": "DEVICE"
        },
        {
          "name": "Routine Asthma Management (in-person and telehealth visits)- Control Group",
          "type": "OTHER"
        },
        {
          "name": "Routine ENT Management (in-person and telehealth visits)- Control Group",
          "type": "OTHER"
        }
      ],
      "intervention_types": [
        "DEVICE",
        "OTHER"
      ],
      "sponsor": "Medentum Innovations",
      "sponsor_class": "INDUSTRY",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": "3 Years",
        "maximum_age": "17 Years",
        "sex": "ALL",
        "summary": "3 Years to 17 Years"
      },
      "enrollment_count": 84,
      "start_date": "2025-10-01",
      "completion_date": "2026-12-01",
      "has_results": false,
      "last_update_posted_date": "2026-03-30",
      "last_synced_at": "2026-10-22T03:03:44.976Z",
      "location_count": 1,
      "location_summary": "Tuscon, Arizona",
      "locations": [
        {
          "city": "Tuscon",
          "state": "Arizona"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07500532"
    },
    {
      "nct_id": "NCT05442203",
      "title": "Electrocardiogram-based Artificial Intelligence-assisted Detection of Heart Disease",
      "overall_status": "UNKNOWN",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Atrial Fibrillation",
        "Structural Heart Disease"
      ],
      "interventions": [
        {
          "name": "Zio Patch Monitor",
          "type": "DEVICE"
        },
        {
          "name": "Echocardiogram",
          "type": "DEVICE"
        }
      ],
      "intervention_types": [
        "DEVICE"
      ],
      "sponsor": "Tempus AI",
      "sponsor_class": "INDUSTRY",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "40 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "40 Years and older"
      },
      "enrollment_count": 1000,
      "start_date": "2022-09-07",
      "completion_date": "2025-07",
      "has_results": false,
      "last_update_posted_date": "2024-07-25",
      "last_synced_at": "2026-10-22T03:03:44.976Z",
      "location_count": 3,
      "location_summary": "Grand Rapids, Michigan • Cincinnati, Ohio • Danville, Pennsylvania",
      "locations": [
        {
          "city": "Grand Rapids",
          "state": "Michigan"
        },
        {
          "city": "Cincinnati",
          "state": "Ohio"
        },
        {
          "city": "Danville",
          "state": "Pennsylvania"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT05442203"
    },
    {
      "nct_id": "NCT07005362",
      "title": "Fitbit and AI Chatbot in Sedentary Primary Care Patients With T2D",
      "overall_status": "COMPLETED",
      "study_type": "OBSERVATIONAL",
      "phases": [],
      "conditions": [
        "Type 2 Diabetes",
        "Type 2 Diabetes Mellitus (T2DM)",
        "T2DM (Type 2 Diabetes Mellitus)",
        "T2D",
        "T2DM",
        "Remote Patient Monitoring",
        "Artificial Intelegence"
      ],
      "interventions": [
        {
          "name": "Fitbit and AI Chatbot",
          "type": "BEHAVIORAL"
        },
        {
          "name": "Routine Care",
          "type": "OTHER"
        }
      ],
      "intervention_types": [
        "BEHAVIORAL",
        "OTHER"
      ],
      "sponsor": "University of Colorado, Denver",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": "80 Years",
        "sex": "ALL",
        "summary": "18 Years to 80 Years"
      },
      "enrollment_count": 35,
      "start_date": "2025-09-03",
      "completion_date": "2026-08-14",
      "has_results": false,
      "last_update_posted_date": "2026-08-19",
      "last_synced_at": "2026-10-22T03:03:44.976Z",
      "location_count": 1,
      "location_summary": "Aurora, Colorado",
      "locations": [
        {
          "city": "Aurora",
          "state": "Colorado"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07005362"
    },
    {
      "nct_id": "NCT06667401",
      "title": "Exploring the Efficacy of Assistive Artificial Intelligence for Ultrasound Guided Regional Anesthesia in Residency Training",
      "overall_status": "COMPLETED",
      "study_type": "OBSERVATIONAL",
      "phases": [],
      "conditions": [
        "Regional Anesthesia"
      ],
      "interventions": [
        {
          "name": "The ScanNav, a novel artificial intelligence device designed to assist in Ultrasound guided regional anesthesia",
          "type": "DEVICE"
        }
      ],
      "intervention_types": [
        "DEVICE"
      ],
      "sponsor": "Medical College of Wisconsin",
      "sponsor_class": "OTHER",
      "healthy_volunteers": null,
      "eligibility": {
        "minimum_age": null,
        "maximum_age": null,
        "sex": "ALL",
        "summary": "Not listed"
      },
      "enrollment_count": 20,
      "start_date": "2025-03-10",
      "completion_date": "2026-01-01",
      "has_results": false,
      "last_update_posted_date": "2026-03-03",
      "last_synced_at": "2026-10-22T03:03:44.976Z",
      "location_count": 1,
      "location_summary": "Milwaukee, Wisconsin",
      "locations": [
        {
          "city": "Milwaukee",
          "state": "Wisconsin"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT06667401"
    },
    {
      "nct_id": "NCT04370002",
      "title": "Sensor-based Characterization of Depression",
      "overall_status": "UNKNOWN",
      "study_type": "OBSERVATIONAL",
      "phases": [],
      "conditions": [
        "Unipolar Depression"
      ],
      "interventions": [],
      "intervention_types": [],
      "sponsor": "Massachusetts General Hospital",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": "75 Years",
        "sex": "ALL",
        "summary": "18 Years to 75 Years"
      },
      "enrollment_count": 100,
      "start_date": "2020-01-28",
      "completion_date": "2024-11-30",
      "has_results": false,
      "last_update_posted_date": "2023-11-03",
      "last_synced_at": "2026-10-22T03:03:44.976Z",
      "location_count": 2,
      "location_summary": "Boston, Massachusetts",
      "locations": [
        {
          "city": "Boston",
          "state": "Massachusetts"
        },
        {
          "city": "Boston",
          "state": "Massachusetts"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT04370002"
    }
  ]
}