---
license: cc-by-nc-4.0
language:
- en
tags:
- healthcare
- endocrinology
- pcos
- polycystic-ovary-syndrome
- fertility
- insulin-resistance
- reproductive-endocrinology
- synthetic-data
- ehr
- clinical
- fhir
pretty_name: "HC-END-008 PCOS Synthetic Dataset (Sample)"
size_categories:
- n<1K
task_categories:
- tabular-classification
- tabular-regression
---

# HC-END-008 — PCOS Synthetic Dataset (Sample)

**XpertSystems.ai · Synthetic Data Factory · Endocrinology Vertical**

A comprehensive synthetic cohort of Polycystic Ovary Syndrome patients organized around the
**Rotterdam phenotypes (A/B/C/D)** and spanning HPO-axis hormonal profiles (LH/FSH, androgens,
AMH), insulin resistance & metabolic syndrome, ovarian morphology (AFC, volume, endometrium),
fertility outcomes (letrozole/clomiphene/IUI/IVF with OHSS risk), pharmacological treatment
trajectories, and long-term cardiometabolic risk. This repository contains a **500-row,
single-seed sample**. The full commercial product scales to 20,000+ patients with 15-year
follow-up trajectories and CSV / Parquet / JSON / **FHIR R4** delivery.

- **SKU:** HC-END-008
- **Sample size:** 500 patients × 190 columns
- **License (sample):** CC-BY-NC-4.0 — commercial license available for the full product
- **Contact:** pradeep@xpertsystems.ai · https://xpertsystems.ai

---

## Validation

This sample passes XpertSystems Grade **A+** validation (overall **10.000 / 10**) with
deterministic reproduction across all six canonical seeds `[42, 7, 123, 2024, 99, 1]`.

Validation philosophy: **structural identities over distribution-fit tests** — including PCOS
physiology checks (hyperandrogenic phenotypes carry higher testosterone). This engine also passes
its own built-in 9-benchmark suite (Azziz phenotype distribution, PPCOS-II letrozole live-birth,
Rotterdam AFC, AMH elevation, HOMA-IR, metabolic syndrome, SART IVF oocytes, depression, LH/FSH).

### Calibration anchors

| Metric | Sample value | Target range | Source |
|---|---|---|---|
| Phenotype A fraction | 34.2% | 31–45% | Azziz 2016 (Rotterdam A ~33-43%) |
| LH/FSH ratio mean | 2.66 | 1.5–3.5 | PCOS LH hypersecretion |
| Elevated AMH fraction | 77.0% | 40–82% | PCOS AMH elevation |
| Mean HOMA-IR | 3.97 | 2.4–4.5 | PCOS insulin resistance |
| Insulin resistance (HOMA≥2.5) | 76.0% | 65–85% | PCOS IR prevalence |
| Metabolic syndrome | 42.4% | 30–50% | PCOS MetS prevalence |
| **Letrozole live-birth rate** | **27.1%** | **24–31%** | PPCOS-II (Legro 2014 NEJM ~27.5%) |
| Depression | 36.8% | 28–42% | PCOS depression prevalence |
| **Testosterone separation (HA−nonHA)** | **30.6 ng/dL** | **≥15** | Hyperandrogenism physiology |
| **AFC in plausible [4,70]** | **100%** | **≥1.0** | Ovarian morphology bounds |
| **TSH in [0.01,10]** | **100%** | **≥1.0** | Assay-range integrity |
| **Column count** | **190** | **≥184** | Schema completeness (9 modules) |

---

## Schema highlights by module (190 columns)

**Demographics.** Age, race (incl. South/East Asian PCOS-relevant strata), height/weight/BMI,
insurance, region.

**Phenotype & diagnosis.** Rotterdam A/B/C/D, hyperandrogenism / oligo-anovulation / PCO-morphology
flags, menstrual pattern & cycle length, Ferriman-Gallwey, hirsutism/acne/alopecia/acanthosis,
diagnosis age & delay.

**Hormonal profile.** LH/FSH & ratio, GnRH pulse frequency, estradiol/estrone/progesterone,
total/free testosterone, SHBG, DHEAS, androstenedione, 17-OHP, DHT, AMH, inhibin B, prolactin,
TSH/FT4, cortisol/ACTH; annual LH/testosterone/AMH JSON trajectories; elevation flags.

**Insulin resistance & metabolic.** Fasting glucose/insulin, HOMA-IR/B, QUICKI, OGTT, HbA1c,
glycemic category, adipokines (adiponectin/leptin/ghrelin), C-peptide, VAI, waist/WHR, full lipid
panel, inflammatory markers, BP, MetS criteria, NAFLD, sleep apnea, HOMA-IR trajectory.

**Ovarian morphology.** AFC (R/L/total), ovarian volume, dominant follicle, stromal ratio &
echogenicity, endometrial thickness/pattern/hyperplasia/cancer, fibroids, hemorrhagic cyst,
Rotterdam AFC & volume criteria.

**Fertility.** Intent, infertility duration, ovulation induction (letrozole/clomiphene/FSH/GnRH),
PPCOS-II-calibrated ovulation & live-birth rates, IUI, IVF (oocytes/fertilization/blastocyst/CPR/
LBR), FET, OHSS risk & events, pregnancy losses, GDM/preeclampsia/preterm/NICU, time-to-conception.

**Pharmacotherapy.** OCP (progestin type, testosterone reduction, SHBG increase), metformin,
spironolactone, GLP-1 RA, inositol, laser/electrolysis, adherence, response, switching.

**Cardiometabolic & long-term risk.** 10yr CVD risk, events, hypertension onset, carotid IMT,
coronary calcium, endothelial dysfunction, endometrial/ovarian/breast cancer, depression/anxiety/
eating disorder, PCOSQ quality of life, sexual dysfunction, body-image distress.

**Clinical labs & utilization.** Vitamin D, ferritin, hemoglobin, LFTs, eGFR, uric acid, heart
rate; visit/referral counts, ultrasound/lab counts, fertility & total costs.

**Coding.** FHIR R4 Patient bundle (full product).

---

## Files

- `hc_end_008_sample.csv` — 500-patient sample (190 columns)
- `generate_sample_dataset_hc_end_008.py` — reproducible generator + validation harness
- `validation_report.json` / `validation_report.md` — full scorecard
- `sweep_summary.json` — 6-seed determinism results

## Loading

```python
import pandas as pd, json
df = pd.read_csv("hc_end_008_sample.csv")
print(df[["patient_id","pcos_phenotype_rotterdam","homa_ir",
          "anti_mullerian_hormone_ng_ml","ovulation_induction_type"]].head())
# Annual trajectories are JSON-encoded:
amh_traj = json.loads(df.loc[0, "amh_trajectory_annual_json"])
```

```python
from datasets import load_dataset
ds = load_dataset("csv", data_files="hc_end_008_sample.csv")
```

## Use cases

- PCOS phenotype classification (Rotterdam A/B/C/D from hormone + morphology features)
- Fertility-outcome modeling (ovulation induction & IVF response prediction)
- Insulin-resistance and metabolic-syndrome risk stratification
- OHSS-risk prediction tooling
- Treatment-response and comparative-effectiveness modeling
- ML training where real PCOS reproductive-endocrine EHR data is PHI-restricted

---

## Honest limitations & disclosed generator behavior

This is a well-calibrated engine (passes its own 9-benchmark suite, correct PCOS physiology). The
following are standard caveats and minor specifics:

1. **Independent symptom/flag draws.** Many clinical flags (acne, alopecia, acanthosis, comorbidity
   flags) are drawn independently conditioned on phenotype, so within-patient symptom clustering is
   weaker than in real cohorts. Phenotype-level prevalences are correct.
2. **Annual trajectories are simplified.** The LH/testosterone/AMH/HOMA-IR JSON arrays are 15-point
   series generated as baseline + small annual noise (AMH with a mild downward drift); they do not
   model treatment-driven inflections or pregnancy-related excursions.
3. **Fertility outcomes are marginal rates.** Letrozole/clomiphene/IVF success fields are
   trial-calibrated population rates rather than individual-conditioned outcomes tied to that
   patient's exact AMH/AFC/age jointly.
4. **Some exclusion conditions are overlays.** Hyperprolactinemia and hypothyroidism are applied as
   independent ~10-12% overlays (as PCOS-mimic exclusions) rather than fully separated diagnoses.

General caveat: cross-field correlations beyond those explicitly modeled may be weaker than in real
cohorts. **Not for clinical decision-making** — research/development use only.

---

## Commercial product comparison

| Capability | This sample | Full HC-END-008 product |
|---|---|---|
| Patients | 500 | 20,000+ (configurable) |
| Follow-up | Baseline + 15pt JSON trajectories | Full 15-year longitudinal panel |
| Seeds / cohorts | 1 | Multi-seed, reproducible |
| Formats | CSV | CSV + Parquet + JSON + **FHIR R4 Bundle** |
| Symptom clustering | Independent draws | Correlated within-patient symptom model |
| Fertility outcomes | Marginal trial rates | Individual-conditioned joint model |
| License | CC-BY-NC-4.0 | Commercial |
| Support & SLA | — | Included |

Full product, custom cohorts, or other endocrinology SKUs: **pradeep@xpertsystems.ai**

---

## Citation

```bibtex
@dataset{xpertsystems_hc_end_008_2026,
  title        = {HC-END-008: PCOS Synthetic Dataset},
  author       = {XpertSystems.ai},
  year         = {2026},
  publisher    = {XpertSystems.ai Synthetic Data Factory},
  url          = {https://xpertsystems.ai},
  note         = {Synthetic; CC-BY-NC-4.0 (sample). Calibrated to: Azziz et al. 2016
                  (PCOS phenotype epidemiology); PPCOS-II / Legro et al. 2014 NEJM
                  (letrozole vs clomiphene for infertility in PCOS); ESHRE/ASRM Rotterdam
                  consensus criteria; SART national IVF outcomes registry; international
                  evidence-based PCOS guideline (Teede et al. 2018/2023).}
}
```

*Synthetic data generated by XpertSystems.ai. Not derived from real patient records.
Not for clinical use.*