Recovery over time
Mean scores · available observations at each visit
PORTFOLIO / SPINE SURGERY
● SYNTHETIC DATAFROM PROCEDURE TO RECOVERY
Spine outcomes, at a glance.
Explore functional recovery and the care journey across a fictional surgical cohort.
A demonstration, built around clinical questions. All patients are fictional. Patterns reflect simulation assumptions and cannot establish treatment effectiveness.
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Procedures in the cohort
Patients by surgical approach
Descriptive distribution; procedure assignment is simulated.
Paired recovery at 6 months
Baseline minus follow-up · patients with recorded 6-month scores
Positive change indicates improvement. No imputation is performed.
Recorded complications
Any recorded perioperative complication
Synthetic categories; follow-up scores are not used to infer complications.
Patient registry
Explore individual records in the filtered cohort
| Patient | Age / sex | Diagnosis | Procedure | Stay | VAS: baseline → 6m | ODI: baseline → 6m | Complication |
|---|
Transparent by design.
Reproducible data. 240 fictional patients generated in Python using seed 2026. No real patient records are used. Procedure allocation, length of stay, complications, and recovery are illustrative assumptions.
Honest denominators. VAS ranges from 0–10 and ODI from 0–100; lower scores indicate less pain or disability. Each visit uses available records. Paired changes require observed baseline and 6-month scores. Missing values are displayed as “Not recorded”.
Technical scope. Python data generation, JavaScript cohort analysis, SVG charts, responsive interface, and CSV export. No predictive model or clinical recommendation is included.