Quick Start

import fairhealth as fh
import numpy as np

# Fairness audit
from fairhealth.fairness.metrics import demographic_parity_diff
y_pred    = np.array([1, 0, 1, 0, 1, 0])
sensitive = np.array([0, 0, 0, 1, 1, 1])
dpd = demographic_parity_diff(y_pred, sensitive)
print(f"DPD: {dpd:.4f}")

# Fuzzy explanation
from fairhealth.explain.fuzzy import get_fired_rules
rules = get_fired_rules(age=42, sbp=145, bs=12, hr=88)
for r in rules:
    print(f"Rule {r['id']}: {r['condition']} -> {r['outcome']}")

# Dengue triage
from fairhealth.lowresource.triage import assess_dengue_risk
result = assess_dengue_risk(age=25, gender="female",
                            area_type="urban", district="Dhaka")
print(result)