⚠️ Loading countdown... until AI crawlers are restricted. Lock in your dataset now.
LIVE DATABASE TICKER: Loading database stats...
DATA at Universal Document
32,667 Physician-Validated Records Oncology · Cardiovascular · Sepsis · Trauma · Stroke · Toxicology ClinicalTrials.gov · PubMed · OpenFDA

Physician-Validated ER Data for AI Training

32,667 records across 6 emergency specialties.

Oncology: 790 | Cardiovascular: 2,158 | Sepsis: 1,122 | Trauma: 29,387 | Stroke: 0 | Toxicology: 0
Physician-Validated ER Records Seeded Live
Last Updated: Loading...

The Data Challenge

The Problem

AI healthcare models drown in noise. PubMed has 30 million articles, making it slow and expensive for engineering teams to curate clean clinical contexts.

Without curation, models risk hallucinating on edge cases and failing clinical safety bars.

The Solution

The ER Dataset — 32,667 Records, 10 Quality Scores, Physician-Validated

Covering 6 emergency specialties:

  • Oncology (790)
  • Cardiovascular (2,158)
  • Sepsis (1,122)
  • Trauma (29,387)
  • Stroke (0)
  • Toxicology (0)

A La Carte Dataset Filtering

Customize your dataset properties before checkout. If no filters are selected, you will receive the full un-truncated dataset.

How It Works

Our rigorous physician validation flow ensures that only high-utility, clinically accurate ER records make it to your training pipeline.

👁️

1. We review every record

Raw records are collected from ClinicalTrials.gov, PubMed, and OpenFDA matching oncology emergency profiles.

✍️

2. Add physician notes

Every record passes 10 hardcoded logic rules assessing study type, data completeness, evidence levels, and ER relevance.

✅ / ❌

3. Approve or reject

Our physicians personally review, annotate, and approve every record on the clinician dashboard.

📥

4. Export curated dataset

We deliver structured datasets in CSV/JSON formats with full scorecard validation matrices and custom notes.

Sample Dataset Preview

A visual representation of the flat database schema and structured physician notes included in every export.

Title: Low-dose low-molecular-weight heparin vs placebo in ambulatory cancer patients.
Condition: Cancer-Associated Thrombosis (CAT)
Evidence Grade: Grade A  |  ER Applicability: 9.2/10  |  Actionability: STAT
Physician Notes (Our Physician Review Team): Data: Double-blind RCT. n=115. RR 0.62 (95% CI 0.45-0.84). p=0.03. Caveats: LMWH requires renal dose adjustment (CrCl <30 mL/min). ER Takeaway: Safe and effective for cancer outpatients. Use in ER triage for thrombosis prevention.

10 Scoring Rules That Filter the Noise

Hardcoded in the validator, not a marketing checklist — every exported record carries its full rule breakdown.

No.RuleWhat it checks
1Precedential ValueSupreme Court (10), Circuit (7-9), District (1-6) precedential weight.
2Circuit SplitFlags whether the case addresses or resolves an active circuit split.
3Loper Bright ImpactRates impact of post-Chevron agency deference challenges.
4Collateral Consequence SeveritySeverity of post-sentence impacts (loss of rights, civil penalties).
5Statutory Interpretation ClarityRates statutory interpretation vs common law evolution.
6Dissent StrengthMeasures the legal weight and volume of the dissenting opinion.
7Amicus BriefsCount and influence of third-party amicus briefs filed.
8Procedural PostureRates the finality of the decision (e.g. preliminary vs final judgment).
9Citation CountNumber of subsequent court decisions citing this record.
10Recency WeightTime-decay weight favouring cases under 3 years old.

Our Legal Review Team

Every record is verified by active legal practitioners with strict case-review standards.

LRT

Our Legal Review Team

Active Legal Scholars & Researchers

- Each record is reviewed by legal researchers with years of appellate and case law analysis experience
- All team members maintain active credentials in legal scholarship and research
- No names listed publicly to protect proprietary review workflows

View Legal Publications on SSRN ↗

What Customers Say

Early feedback from health AI teams training on our structured emergency datasets.

"Having physician-verified notes saved our engineers hundreds of hours."

— Lead AI Scientist, HealthTech Unicorn

"The 10-rule scorecard allowed us to filter out noise instantly."

— Director of Pharmacovigilance, Global Pharma

Dataset specifications & pricing tiers

All tiers are physician-reviewed. Every record ships with its full 10-rule scorecard.

Mini

Free / 50 records
  • Level 2 reviewed sample
  • Requires email verification
  • Manual review & approval

Growth

$3,500 / 500 records
  • Level 2/3 mixed, audit-grade top records flagged
  • Priority condition weighting available on request
  • CSV + JSON delivery

Frequently Asked Questions

Q: Who validates the data?

A: Our legal review team personally reviews and grades every case record. No automated validation shortcut is used. Every team member has extensive legal expertise.

Q: What sources are used?

A: PACER, BOP, and Federal Court registries. We verify and annotate high-yield cases across 6 legal specialties.

Q: Is this data suitable for AI training?

A: Yes. Our datasets are designed to reduce AI hallucinations by providing attorney-reviewed, high-quality training data that filters out noise and low-precedential cases.

Q: What format is the data in?

A: CSV and JSON, ready for any AI pipeline. We also offer UDS (Universal Document) format for customers requiring cryptographic verification.

Q: How many records are currently available?

A: 32,667 records across multiple federal court categories (Sentencing, Habeas Corpus, Prison Conditions, Civil Rights, Administrative Law, and Constitutional Law).

Q: Why is the pre-September 15th snapshot important?

A: Major legal database platforms are implementing new restrictions on AI crawlers starting September 15, 2026. Our pre-September dataset captures the last comprehensive snapshot of public federal court litigation. After this date, new records will be significantly harder to obtain.

Ready to Train Your AI on Attorney-Reviewed Data?

Contact Our Curation Team

We typically respond within 4 business hours.