| --- |
| 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.* |
|
|
