{
  "api_version": "1",
  "request": {
    "url": "https://clinicaltrialsfind.com/api/v1/search.json?condition=Machine+Learning&page=4",
    "query": {
      "condition": "Machine Learning",
      "page": 4
    },
    "page_size": 10
  },
  "pagination": {
    "page": 4,
    "page_size": 10,
    "total_count": 256,
    "total_pages": 26,
    "next_page_url": "https://clinicaltrialsfind.com/api/v1/search.json?condition=Machine+Learning&page=5&page_size=10",
    "previous_page_url": "https://clinicaltrialsfind.com/api/v1/search.json?condition=Machine+Learning&page=3&page_size=10"
  },
  "source": "remote",
  "last_synced_at": "2026-10-27T08:49:50.411Z",
  "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": "NCT04604457",
      "title": "Impact of Predictive Modeling on Time to Palliative Care in an Outpatient Primary Care Population",
      "overall_status": "COMPLETED",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Palliative Care"
      ],
      "interventions": [
        {
          "name": "Palliative care contacts primary care",
          "type": "OTHER"
        }
      ],
      "intervention_types": [
        "OTHER"
      ],
      "sponsor": "Mayo Clinic",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "18 Years and older"
      },
      "enrollment_count": 127070,
      "start_date": "2020-08-31",
      "completion_date": "2021-05-31",
      "has_results": false,
      "last_update_posted_date": "2021-06-16",
      "last_synced_at": "2026-10-27T08:49:50.411Z",
      "location_count": 1,
      "location_summary": "Rochester, Minnesota",
      "locations": [
        {
          "city": "Rochester",
          "state": "Minnesota"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT04604457"
    },
    {
      "nct_id": "NCT05034302",
      "title": "Posture Analysis Through Machine Learning",
      "overall_status": "UNKNOWN",
      "study_type": "OBSERVATIONAL",
      "phases": [],
      "conditions": [
        "Health Behavior"
      ],
      "interventions": [],
      "intervention_types": [],
      "sponsor": "SentiMetrix, Inc",
      "sponsor_class": "INDUSTRY",
      "healthy_volunteers": null,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": "85 Years",
        "sex": "ALL",
        "summary": "18 Years to 85 Years"
      },
      "enrollment_count": 20,
      "start_date": "2021-11-01",
      "completion_date": "2022-06-30",
      "has_results": false,
      "last_update_posted_date": "2022-05-10",
      "last_synced_at": "2026-10-27T08:49:50.411Z",
      "location_count": 1,
      "location_summary": "San Luis Obispo, California",
      "locations": [
        {
          "city": "San Luis Obispo",
          "state": "California"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT05034302"
    },
    {
      "nct_id": "NCT07318233",
      "title": "Adaptive Self-Efficacy-Based AI Coaching for Cycling",
      "overall_status": "RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Exercise Training",
        "Exercise Behavior",
        "Exercise Adherence Challenges",
        "Motivation for Physical Activity",
        "Motivational Enhancement"
      ],
      "interventions": [
        {
          "name": "Group 1: Self-efficacy-based AI coaching",
          "type": "BEHAVIORAL"
        },
        {
          "name": "Group 2: Static AI Affirmations",
          "type": "BEHAVIORAL"
        }
      ],
      "intervention_types": [
        "BEHAVIORAL"
      ],
      "sponsor": "University of Miami",
      "sponsor_class": "OTHER",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": "40 Years",
        "sex": "ALL",
        "summary": "18 Years to 40 Years"
      },
      "enrollment_count": 120,
      "start_date": "2026-05-15",
      "completion_date": "2028-12-28",
      "has_results": false,
      "last_update_posted_date": "2026-08-17",
      "last_synced_at": "2026-10-27T08:49:50.411Z",
      "location_count": 1,
      "location_summary": "Coral Gables, Florida",
      "locations": [
        {
          "city": "Coral Gables",
          "state": "Florida"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07318233"
    },
    {
      "nct_id": "NCT07669168",
      "title": "Health Ahead Comparative Effectiveness Study",
      "overall_status": "RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Health Services Accessibility",
        "Rural Health",
        "Medically Underserved Area",
        "Preventive Health Services",
        "Patient Participation",
        "Health Behavior",
        "Aging",
        "Cardiovascular Diseases",
        "Metabolic Syndrome",
        "Cognitive Dysfunction",
        "Frailty",
        "Activities of Daily Living",
        "Health Related Quality of Life",
        "Health Equity",
        "Telemedicine"
      ],
      "interventions": [
        {
          "name": "AI-Assisted Screening Interpretation (AI Reads)",
          "type": "BEHAVIORAL"
        },
        {
          "name": "Human-Only Screening Interpretation",
          "type": "BEHAVIORAL"
        }
      ],
      "intervention_types": [
        "BEHAVIORAL"
      ],
      "sponsor": "William Brandenburg, MD",
      "sponsor_class": "INDUSTRY",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "18 Years and older"
      },
      "enrollment_count": 1000000,
      "start_date": "2026-06-09",
      "completion_date": "2099-12-31",
      "has_results": false,
      "last_update_posted_date": "2026-09-08",
      "last_synced_at": "2026-10-27T08:49:50.411Z",
      "location_count": 1,
      "location_summary": "Boulder, Colorado",
      "locations": [
        {
          "city": "Boulder",
          "state": "Colorado"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07669168"
    },
    {
      "nct_id": "NCT06395636",
      "title": "Early Detection of Infection Using the Fitbit in Pediatric Surgical Patients",
      "overall_status": "RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Appendectomy",
        "Appendicitis",
        "Appendicitis Acute"
      ],
      "interventions": [
        {
          "name": "Infection-Prediction Algorithm",
          "type": "DEVICE"
        }
      ],
      "intervention_types": [
        "DEVICE"
      ],
      "sponsor": "Ann & Robert H Lurie Children's Hospital of Chicago",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "3 Years",
        "maximum_age": "18 Years",
        "sex": "ALL",
        "summary": "3 Years to 18 Years"
      },
      "enrollment_count": 500,
      "start_date": "2025-01-07",
      "completion_date": "2027-06-30",
      "has_results": false,
      "last_update_posted_date": "2026-05-13",
      "last_synced_at": "2026-10-27T08:49:50.411Z",
      "location_count": 4,
      "location_summary": "Chicago, Illinois • Maywood, Illinois • Winfield, Illinois",
      "locations": [
        {
          "city": "Chicago",
          "state": "Illinois"
        },
        {
          "city": "Chicago",
          "state": "Illinois"
        },
        {
          "city": "Maywood",
          "state": "Illinois"
        },
        {
          "city": "Winfield",
          "state": "Illinois"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT06395636"
    },
    {
      "nct_id": "NCT05338905",
      "title": "Intensive Symptom Surveillance Guided by Machine Learning-Directed Risk Stratification in Patients With Non-Metastatic Head and Neck Cancer, The INSIGHT Trial",
      "overall_status": "ACTIVE_NOT_RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Head and Neck Squamous Cell Carcinoma"
      ],
      "interventions": [
        {
          "name": "Palliative Therapy",
          "type": "OTHER"
        },
        {
          "name": "Quality-of-Life Assessment",
          "type": "OTHER"
        },
        {
          "name": "Questionnaire Administration",
          "type": "OTHER"
        }
      ],
      "intervention_types": [
        "OTHER"
      ],
      "sponsor": "Roswell Park Cancer Institute",
      "sponsor_class": "OTHER",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "18 Years and older"
      },
      "enrollment_count": 72,
      "start_date": "2022-10-11",
      "completion_date": "2027-12-17",
      "has_results": false,
      "last_update_posted_date": "2026-01-23",
      "last_synced_at": "2026-10-27T08:49:50.411Z",
      "location_count": 1,
      "location_summary": "Buffalo, New York",
      "locations": [
        {
          "city": "Buffalo",
          "state": "New York"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT05338905"
    },
    {
      "nct_id": "NCT02265354",
      "title": "Developing Smokers for Smoker (S4S): A Collective Intelligence Tailoring System",
      "overall_status": "COMPLETED",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "NA"
      ],
      "conditions": [
        "Tobacco Smoking"
      ],
      "interventions": [
        {
          "name": "Collective-Intelligence computer tailored health communication",
          "type": "BEHAVIORAL"
        },
        {
          "name": "Rule-based computer tailored health communication",
          "type": "BEHAVIORAL"
        }
      ],
      "intervention_types": [
        "BEHAVIORAL"
      ],
      "sponsor": "University of Massachusetts, Worcester",
      "sponsor_class": "OTHER",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": "19 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "19 Years and older"
      },
      "enrollment_count": 260,
      "start_date": "2017-01-11",
      "completion_date": "2020-06-28",
      "has_results": false,
      "last_update_posted_date": "2020-10-08",
      "last_synced_at": "2026-10-27T08:49:50.411Z",
      "location_count": 1,
      "location_summary": "Worcester, Massachusetts",
      "locations": [
        {
          "city": "Worcester",
          "state": "Massachusetts"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT02265354"
    },
    {
      "nct_id": "NCT05010655",
      "title": "Low Ejection Fraction in Single Lead ECG",
      "overall_status": "COMPLETED",
      "study_type": "OBSERVATIONAL",
      "phases": [],
      "conditions": [
        "Left Ventricular Dysfunction",
        "Ventricular Dysfunction",
        "Heart Diseases",
        "Cardiovascular Diseases"
      ],
      "interventions": [
        {
          "name": "Use of Eko DUO Electronic Stethoscope",
          "type": "DEVICE"
        }
      ],
      "intervention_types": [
        "DEVICE"
      ],
      "sponsor": "Eko Devices, Inc.",
      "sponsor_class": "INDUSTRY",
      "healthy_volunteers": true,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "18 Years and older"
      },
      "enrollment_count": 1935,
      "start_date": "2021-06-01",
      "completion_date": "2022-05-24",
      "has_results": false,
      "last_update_posted_date": "2022-12-09",
      "last_synced_at": "2026-10-27T08:49:50.411Z",
      "location_count": 2,
      "location_summary": "O'Fallon, Illinois • Springfield, Illinois",
      "locations": [
        {
          "city": "O'Fallon",
          "state": "Illinois"
        },
        {
          "city": "Springfield",
          "state": "Illinois"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT05010655"
    },
    {
      "nct_id": "NCT07227233",
      "title": "Artificial Intelligence and Machine Learning to Guide CDK4/6 Inhibitor Rechallenge in Breast Cancer.",
      "overall_status": "RECRUITING",
      "study_type": "INTERVENTIONAL",
      "phases": [
        "PHASE2"
      ],
      "conditions": [
        "Breast Cancer"
      ],
      "interventions": [
        {
          "name": "A CDK4/6 inhibitor different from the first that the participant had received, plus fulvestrant.",
          "type": "DRUG"
        },
        {
          "name": "Treatment of physician's choice",
          "type": "DRUG"
        }
      ],
      "intervention_types": [
        "DRUG"
      ],
      "sponsor": "University of California, San Diego",
      "sponsor_class": "OTHER",
      "healthy_volunteers": false,
      "eligibility": {
        "minimum_age": "18 Years",
        "maximum_age": null,
        "sex": "ALL",
        "summary": "18 Years and older"
      },
      "enrollment_count": 105,
      "start_date": "2026-03-31",
      "completion_date": "2028-12",
      "has_results": false,
      "last_update_posted_date": "2026-04-09",
      "last_synced_at": "2026-10-27T08:49:50.411Z",
      "location_count": 1,
      "location_summary": "La Jolla, California",
      "locations": [
        {
          "city": "La Jolla",
          "state": "California"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT07227233"
    },
    {
      "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": "2026-10-27T08:49:50.411Z",
      "location_count": 1,
      "location_summary": "Houston, Texas",
      "locations": [
        {
          "city": "Houston",
          "state": "Texas"
        }
      ],
      "official_url": "https://clinicaltrials.gov/study/NCT05775133"
    }
  ]
}