napix-synthetic 1.0.0

Professional SDK for generating synthetic physiological data for AI training

NAPIX Synthetic Data Generator

A professional SDK for generating synthetic physiological data for AI training and simulation.

Quick Start

from napix_synthetic import SyntheticDataGenerator, ScenarioConfig

config = ScenarioConfig(
    organ="cardiovascular",
    severity=0.7,
    duration_minutes=30.0,
    dt=0.1
)

generator = SyntheticDataGenerator(config)
df = generator.generate()

print(df.head())

Features

• Severity‑Controlled Trends — Deterioration rate scales with severity (0.0–1.0)
• Physiological Realism — MAP drops, HR rises, lactate climbs exponentially under shock
• Shock State Progression — compensated → decompensated → irreversible
• Collapse Risk Metric — 0–99% risk score aligned to trajectory
• Configurable Duration & Resolution — Control minutes and sampling interval

Installation

pip install napix-synthetic

Use Cases

• AI Training — Generate labelled shock trajectories for ML models
• Simulation Testing — Validate clinical decision support algorithms
• Education — Teach hemodynamic deterioration patterns
• Benchmarking — Compare predictor performance on controlled synthetic data

License

MIT