AI in clinical trials landscape (monthly)

Name: AI in clinical trials landscape (monthly)
Creator: ClinicalTrials.gov (U.S. National Library of Medicine)
License: https://clinicaltrials.gov/about-site/terms-conditions
Keywords: clinical-trials, ai, machine-learning, health, research, signals, monthly

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Query in workbench

Sample onlyDownload sample CSV Download sample JSONSample rows only (up to 20) — not the complete dataset.

Every study on ClinicalTrials.gov (U.S. National Library of Medicine) that genuinely involves artificial intelligence — AI as the tested intervention, AI in the title, or AI in the study summary/description — with AI-role classification, therapeutic-area categorization (18 areas, documented first-match-wins keyword rules), sponsor and country normalization (ISO alpha-3, hub.normalize + 3 documented aliases), and a documented 0-100 trial-activity score (0.6*liveliness + 0.4*recency + results bonus) ranked as activity_rank. Collection: keyless official ClinicalTrials.gov v2 API, broad phrase query over the full registry; an AI-term verification regex then drops the API's tokenization false positives (~48% of raw hits, counted not fabricated). Columns: as-of month, NCT id (primary key), title, ai_role, therapeutic_area, status, study_type, phase, start year/month, lead sponsor + class, lead country code (ISO alpha-3 join key) + full country list + count, enrollment, results-posted flag, primary condition, intervention types, activity score/rank, per-row ClinicalTrials.gov URL, row hash. Monthly cadence; month-granular as-of stamping makes identical input hash identical. Caveats: sponsor-submitted data (statuses lag; 1,780 UNKNOWN at 2026-09), keyword heuristics not clinical adjudication, phases mostly NA for device/software AI studies. Agent-curated by intel-1 (2026-09-25T09:10Z). commercial_use = unclear: ClinicalTrials.gov data are free to all requesters with attribution + processing-date display + modification disclosure; records may carry third-party (sponsor) copyright outside the U.S. Sample use: filter ai_role = 'ai_intervention' and status = 'recruiting' for the live AI-device trial pipeline, or group by therapeutic_area for where clinical AI research concentrates.

Source: ClinicalTrials.gov (U.S. National Library of Medicine)
Rows: 5,550
Columns: 23
Source cadence: Monthly
Last refreshed: Sep 25, 2026
Theme: health

Column	Type	Description
as_of	string	Fixed as-of month of the run (YYYY-MM). Month-granular stamping so identical input produces an identical content hash; doubles as the processing date ClinicalTrials.gov terms require distributors to show. (unit: month)
nct_id	string	ClinicalTrials.gov identifier (NCT number). The primary key; dedupe is on this id.
title	string	Study brief title (official title when the brief title is empty), sponsor-submitted free text.
ai_role	string	Where AI genuinely appears, first-match-wins by evidence strength: ai_intervention (phrase in an intervention name — AI is being tested), ai_in_title, ai_in_summary (brief summary), ai_in_description (detailed description only). Rows with no genuine AI phrase match are dropped by the verification screen, never published.
therapeutic_area	string	One of 18 areas (oncology, cardiology, neurology, psychiatry, infectious_disease, endocrinology, respiratory, gastroenterology, nephrology, musculoskeletal, dermatology, ophthalmology, obstetrics_gynecology, pediatrics, dentistry, surgery, emergency_critical_care, other) assigned by documented first-match-wins keyword rules over the condition list — a heuristic, not clinical adjudication.
status	string	Normalized recruitment status (recruiting, active_not_recruiting, not_yet_recruiting, enrolling_by_invitation, completed, terminated, withdrawn, suspended, unknown, no_longer_available). Sponsor-reported and often lagging (many UNKNOWN).
study_type	string	interventional, observational, or expanded_access (lowercased registry value).
phase	string	Normalized phase (phase_1..phase_4, early_phase_1, na, unknown; multi-phase joined with '+'). Mostly NA — device/software AI studies rarely declare drug phases.
start_year	integer	Study start year parsed from the registry start date (YYYY, YYYY-MM, or YYYY-MM-DD); null when absent. (unit: year)
start_month	string	Study start month (YYYY-MM); null when the registry gives year-only or no date. (unit: month)
lead_sponsor	string	Lead sponsor name as submitted (free text, not canonicalized across spelling variants).
sponsor_class	string	Registry sponsor class, lowercased (industry, nih, other_gov, fed, network, other, unknown).
lead_country_code	string	ISO alpha-3 code of the first listed study location's country (hub.normalize + 3 documented aliases). The join key for country-level analysis; null when no locations are listed.
countries	string	Sorted, deduped ISO alpha-3 codes of all study locations, '\|' separated.
n_countries	integer	Number of distinct study countries. (unit: count)
enrollment	integer	Sponsor-reported target enrollment count; null when the registry carries none. (unit: count)
has_results	boolean	True when the registry shows a results first-posted date for the study. (unit: boolean)
primary_condition	string	First condition in the registry condition list (free text).
intervention_types	string	Sorted unique registry intervention types (device, behavioral, diagnostic_test, drug, procedure, ...), '\|' separated, lowercased; empty when none are listed.
activity_score	float	Documented 0-100 trial-activity score: 0.6 * status liveliness weight (recruiting 100 … withdrawn 10) + 0.4 * recency weight (start within 12/24/36 months of as_of: 100/60/30/10) + 5 when results are posted, capped at 100. (unit: score)
activity_rank	integer	Rank by activity_score (ties by NCT id). 1 = most active AI trial this month. (unit: rank)
source_url	string	Per-row link to the study's ClinicalTrials.gov record. (unit: URL)
row_hash	string	SHA-256 (16 hex chars) over the row's content fields; identical input yields an identical hash, so a re-run on unchanged registry content is a no-op. (unit: hash)

First 10 sample rows — a preview, not the complete dataset.

as_of	nct_id	title	ai_role	therapeutic_area	status	study_type	phase	start_year	start_month	lead_sponsor	sponsor_class	lead_country_code	countries	n_countries	enrollment	has_results	primary_condition	intervention_types	activity_score	activity_rank	source_url	row_hash
2026-09	NCT05286034	Using Artificial Intelligence-based ChatBot to Improve Women's Participation to Cervical Cancer Screening Programme	ai_intervention	oncology	recruiting	interventional	na	2,025	2025-11	International Agency for Research on Cancer	other	FRA	FRA	1	3,000	false	Cervical Cancer Screening	behavioral	100	1	https://clinicaltrials.gov/study/NCT05286034	6f16c7d00148ec67
2026-09	NCT05652361	Machine Learning-based Surgical Guidance System for Robot-assisted Rectal Surgery	ai_in_title	oncology	recruiting	interventional	na	2,026	2026-02	Technische Universität Dresden	other	DEU	DEU	1	12	false	Rectum Cancer	other	100	2	https://clinicaltrials.gov/study/NCT05652361	34e2d7cdf5a4895b
2026-09	NCT05913843	DeciFace: Decipher the Influence of Ethnic Backgrounds on the Facial Dysmorphic Features of Rare Mendelian Disorders	ai_in_summary	other	recruiting	observational	unknown	2,025	2025-11	National Taiwan University Hospital	other	TWN	TWN	1	100	false	Rare Diseases	device	100	3	https://clinicaltrials.gov/study/NCT05913843	586cbc514f5ce46c
2026-09	NCT06061822	Artificial Intelligence Delivered Cardiac Magnetic Resonance - Prospective Validation	ai_in_title	cardiology	recruiting	interventional	na	2,026	2026-05	Imperial College London	other	GBR	GBR	1	150	false	Cardiovascular Diseases	diagnostic_test	100	4	https://clinicaltrials.gov/study/NCT06061822	60e98f5cab7aa8ab
2026-09	NCT06381921	Objective Integrated Multimodal Electrophysiological Index for the Quantification of Visceral Pain	ai_in_description	other	recruiting	interventional	na	2,025	2025-09	University of Connecticut	other	USA	USA	1	120	false	Abdominal Pain	behavioral	100	5	https://clinicaltrials.gov/study/NCT06381921	aaf554e72f4d0e09
2026-09	NCT06382038	Smart Technology Facilitated Patient-centered Care for Patients With Pulmonary Thromboembolism	ai_in_summary	respiratory	recruiting	interventional	na	2,026	2026-08	Navy General Hospital, Beijing	other	CHN	CHN	1	2,972	false	Venous Thromboembolism	other	100	6	https://clinicaltrials.gov/study/NCT06382038	8db7535d8df3c9ce
2026-09	NCT06418971	Testing & Refinement of CarePair: An Assessment and Referral Platform to Support Family Caregivers of Alzheimer's Disease and Related Dementias.	ai_in_description	neurology	recruiting	interventional	na	2,025	2025-09	University of Southern California	other	USA	USA	1	80	false	Caregiver Burden	behavioral	100	7	https://clinicaltrials.gov/study/NCT06418971	2120233f0ff2d70c
2026-09	NCT06459427	A Multicenter, RAndomIzed, coNtrolled, umBrella Trial fOr Minimally Invasive Neurosurgery With AI-assisted Robotic guidanCe for Hemorrhagic Stroke	ai_in_summary	neurology	recruiting	interventional	na	2,026	2026-05	Yanbing Yu	other	CHN	CHN	1	142	false	Brain Stem Hemorrhage	other\|procedure	100	8	https://clinicaltrials.gov/study/NCT06459427	122bf0610060237b
2026-09	NCT06465719	A Trial for Minimally Invasive Neurosurgery With AI-assisted Robotic Guidance for Moderate Basal Ganglia Hemorrhage (RAINBOW-MBH)	ai_in_summary	other	recruiting	interventional	na	2,025	2025-09	Second Affiliated Hospital, Zhejiang University, School of Medicine	other	CHN	CHN	1	330	false	Basal Ganglia Hemorrhage	drug\|procedure	100	9	https://clinicaltrials.gov/study/NCT06465719	9b42a10c1a4ff9e7
2026-09	NCT06492486	Glioma Adaptive Radiotherapy With Development of an Artificial Intelligence Workflow	ai_in_title	other	recruiting	interventional	phase2	2,026	2026-07	Tata Memorial Centre	other	IND	IND	1	60	false	Diffuse Glioma	radiation	100	10	https://clinicaltrials.gov/study/NCT06492486	b710cb01d8f6f347

Profiled Sep 25, 2026 from snapshot 20260925T093808Z-b6ae3ba86c11

Measured

Completeness: 99.5%
Rows: 5,550
Columns: 23
Columns with gaps: 4

Column	Missing	Distinct	Range	Distribution
as_ofvarchar	0%	1	—	2026-095,550
nct_idvarchar	0%	6,302	—	NCT000395851 NCT000495561 NCT002410461
titlevarchar	0%	4,438	—	Artificial Intelligence and Bowel Cleansing Quality2 Artificial Intelligence in Colonoscopy2 Smart Technology Facilitated Patient-centered Venous Thromboembolism Management2
ai_rolevarchar	0%	4	—	ai_in_title2,507 ai_in_summary2,068 ai_intervention513
therapeutic_areavarchar	0%	17	—	other1,744 oncology1,109 cardiology616
statusvarchar	0%	9	—	completed1,677 recruiting1,330 unknown1,110
study_typevarchar	0%	3	—	observational3,241 interventional2,308 expanded_access1
phasevarchar	0%	10	—	unknown3,243 na2,157 phase257
start_yearbigint	0.07%	32	1,998 → 2,029median 2,023	72 outside 1st–99th percentile
start_monthvarchar	0.07%	238	—	2026-06118 2026-09113 2026-03111
lead_sponsorvarchar	0%	2,756	—	National Taiwan University Hospital55 Sun Yat-sen University51 Mayo Clinic50
sponsor_classvarchar	0%	5	—	other4,836 industry468 other_gov189
lead_country_codevarchar	10.9%	117	—	CHN1,180 USA924 FRA293
countriesvarchar	0%	252	—	CHN1,167 USA864 603
n_countriesbigint	0%	13	0 → 19median 1	40 outside 1st–99th percentile
enrollmentbigint	0.13%	1,049	0 → 50,000,000median 233	53 outside 1st–99th percentile
has_resultsboolean	0%	2	—	false5,434 true116
primary_conditionvarchar	0%	2,901	—	Breast Cancer88 Artificial Intelligence70 Heart Failure57
intervention_typesvarchar	0%	66	—	other1,366 1,182 device878
activity_scoredouble	0%	37	7 → 100median 48	48 outside 1st–99th percentile
activity_rankbigint	0%	5,661	1 → 5,550median 2,776	112 outside 1st–99th percentile
source_urlvarchar	0%	5,550	—	https://clinicaltrials.gov/study/NCT000395851 https://clinicaltrials.gov/study/NCT000495561 https://clinicaltrials.gov/study/NCT002410461
row_hashvarchar	0%	5,274	—	0006e8b69c04d9cb1 0008a0906640aad41 00251815d95a54371

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/ai_clinical_trial_signals/ai_clinical_trials_monthly" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/ai_clinical_trial_signals/ai_clinical_trials_monthly").json()
print(ds["title"], ds["rows"], "rows")

# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
    print(row)

API endpoint: https://datazimuts.com/v1/datasets/ai_clinical_trial_signals/ai_clinical_trials_monthly

Tip: fetch /llms.txt for the full machine-readable catalog.

Cite this snapshot

Pinned to snapshot 20260925T093808Z-b6ae3ba86c11 and its content hash, so readers get exactly the data you used.

APA

ClinicalTrials.gov (U.S. National Library of Medicine). (2026). AI in clinical trials landscape (monthly) [Data set, snapshot 20260925T093808Z-b6ae3ba86c11, sha256 b6ae3ba86c11]. Datazimuts. Retrieved 2026-09-25, from https://datazimuts.com/en/datasets/ai_clinical_trial_signals/ai_clinical_trials_monthly?snapshot=20260925T093808Z-b6ae3ba86c11

BibTeX

@misc{dz_ai_clinical_trial_signals_ai_clinical_tr_b6ae3ba8,
  title        = {{AI in clinical trials landscape (monthly)}},
  author       = {{ClinicalTrials.gov (U.S. National Library of Medicine)}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/en/datasets/ai_clinical_trial_signals/ai_clinical_trials_monthly?snapshot=20260925T093808Z-b6ae3ba86c11}},
  note         = {Snapshot 20260925T093808Z-b6ae3ba86c11, sha256 b6ae3ba86c11d08585f554cd053cad8e43d29301db898b9e8e915f8941705fae; accessed 2026-09-25}
}

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AI in clinical trials landscape (monthly)

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