autoprognosis.plugins.prediction.risk_estimation.benchmarks.cvd.aha.model module

class AHAModel

Bases: object

fit(*args: Any, **kwargs: Any) → AHAModel
predict(df: DataFrame, times: list = []) → DataFrame
score(X: DataFrame, Y: DataFrame) → float
inference(gender: str = 'F', age: int = 55, tchol: float = 213, hdlc: float = 50, sbp: float = 120, smoking: bool = False, diab: bool = False, ht_treat: bool = False, race: str = 'W') → float
Parameters:

  • gender – ‘F’ or ‘M’

  • age

  • tchol – total cholesterol

  • hdlc

  • sbp – blood pressue

  • smoking – 0 or 1

  • diab – 0 or 1 (can be more than 1)

:param ht_treat:0 or 1 :param race: :return:

mmolL_to_mgdl(val: float) → float