{
  "api_version": "1",
  "request": {
    "url": "https://clinicaltrialsfind.com/api/v1/search.json?intervention=Green+Learning+Artificial+Intelligence",
    "query": {
      "intervention": "Green Learning Artificial Intelligence"
    },
    "page_size": 10
  },
  "pagination": {
    "page": 1,
    "page_size": 10,
    "total_count": 3,
    "total_pages": 1,
    "next_page_url": null,
    "previous_page_url": null
  },
  "source": "remote",
  "last_synced_at": "2026-09-05T00:42:55.082Z",
  "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": "NCT06779617",
      "title": "UMMS Sepsis Early Prediction Score (SEPSys) and RESCUE Score Combined Clinical Trial",
      "overall_status": "RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Sepsis",
        "Patient Deterioration"
      ],
      "interventions": [
        {
          "name": "SEPSys",
          "type": "DEVICE"
        },
        {
          "name": "RESCUE",
          "type": "DEVICE"
        }
      ],
      "intervention_types": [
        "DEVICE"
      ],
      "sponsor": "University of Maryland, Baltimore",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "18 Years and older"
      },
      "enrollment_count": 150000,
      "start_date": "2026-02-01",
      "completion_date": "2028-12",
      "has_results": false,
      "last_update_posted_date": "2026-05-05",
      "last_synced_at": "2026-09-05T00:42:55.082Z",
      "location_count": 8,
      "location_summary": "Baltimore, Maryland • Bel Air, Maryland • Easton, Maryland + 4 more",
      "locations": [
        {
          "city": "Baltimore",
          "state": "Maryland"
        },
        {
          "city": "Baltimore",
          "state": "Maryland"
        },
        {
          "city": "Bel Air",
          "state": "Maryland"
        },
        {
          "city": "Easton",
          "state": "Maryland"
        },
        {
          "city": "Glen Burnie",
          "state": "Maryland"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT06779617"
    },
    {
      "nct_id": "NCT07162194",
      "title": "MRI-Based Machine Learning Approach Versus Radiologist MRI Reading for the Detection of Prostate Cancer, The PRIMER Trial",
      "overall_status": "RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Prostate Carcinoma"
      ],
      "interventions": [
        {
          "name": "Targeted Prostate Biopsy",
          "type": "PROCEDURE"
        },
        {
          "name": "Prostate Imaging Reporting & Data System",
          "type": "DIAGNOSTIC_TEST"
        },
        {
          "name": "Deep Learning Artificial Intelligence",
          "type": "DIAGNOSTIC_TEST"
        },
        {
          "name": "Green Learning Artificial Intelligence",
          "type": "DIAGNOSTIC_TEST"
        },
        {
          "name": "Radical Prostatectomy",
          "type": "PROCEDURE"
        }
      ],
      "intervention_types": [
        "PROCEDURE",
        "DIAGNOSTIC_TEST"
      ],
      "sponsor": "University of Southern California",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "20 Years",
        "maximum_age": null,
        "sex": "MALE",
        "summary": "20 Years and older · Male only"
      },
      "enrollment_count": 130,
      "start_date": "2025-09-19",
      "completion_date": "2028-10-15",
      "has_results": false,
      "last_update_posted_date": "2026-09-01",
      "last_synced_at": "2026-09-05T00:42:55.082Z",
      "location_count": 1,
      "location_summary": "Los Angeles, California",
      "locations": [
        {
          "city": "Los Angeles",
          "state": "California"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07162194"
    },
    {
      "nct_id": "NCT05775133",
      "title": "Feasibility and Utility of Artificial Intelligence (AI) / Machine Learning (ML) - Driven Advanced Intraoperative Visualization and Identification of Critical Anatomic Structures and Procedural Phases in Laparoscopic Cholecystectomy",
      "overall_status": "UNKNOWN",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Cholecystitis",
        "Cholelithiasis",
        "Biliary Dyskinesia"
      ],
      "interventions": [
        {
          "name": "ICG",
          "type": "DEVICE"
        }
      ],
      "intervention_types": [
        "DEVICE"
      ],
      "sponsor": "Activ Surgical",
      "sponsor_class": "INDUSTRY",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "18 Years and older"
      },
      "enrollment_count": 120,
      "start_date": "2023-08-01",
      "completion_date": "2025-12",
      "has_results": false,
      "last_update_posted_date": "2024-02-21",
      "last_synced_at": "2026-09-05T00:42:55.082Z",
      "location_count": 1,
      "location_summary": "Houston, Texas",
      "locations": [
        {
          "city": "Houston",
          "state": "Texas"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT05775133"
    }
  ]
}