demo.py

import json

from OHA.Diabetes import Diabetes
from OHA.Framingham import Framingham
from OHA.HEARTS import HEARTS
from OHA.HealthAssessment import HealthAssessment as HA
from OHA.SgFramingham import SgFramingham
from OHA.SingHealth import SingHealth
from OHA.WHO import WHO
from OHA.param_builders.diabetes_param_builder import DiabetesParamsBuilder as DBP
from OHA.param_builders.framingham_param_builder import FraminghamParamsBuilder as FPB
from OHA.param_builders.sg_framingham_param_builder import SGFraminghamParamsBuilder as SGFPB
from OHA.param_builders.who_param_builder import WhoParamsBuilder as WPB

print('--- Diabetes Risk Demo ---\n')
params = DBP() \
    .gender('M').age(40).sbp(150).dbp(92).weight(92, 'kg').height(1.5, 'm').waist(50, 'cm').hip(90, 'cm').build()
result = Diabetes().calculate(params)
print('--> Diabetes:', result)
print()

print('--- Framingham Risk Demos ---\n')
params = FPB().gender('M').age(50).t_chol(300, 'mg/dl').hdl_chol(60, 'mg/dl') \
    .sbp(110).smoker(True).diabetic(False).bp_medication(False).build()
result = Framingham().calculate(params)
print('--> Framingham:', result)
print()

params = FPB().gender('F').age(70).t_chol(170, 'mg/dl').hdl_chol(45, 'mg/dl').sbp(125).build()
result = Framingham().calculate(params)
print('--> Framingham:', result)
print()

print('--- WHO/ISH Risk Demos ---\n')
params = WPB().gender("M").age(50).sbp1(120).sbp2(140).chol(5.2, 'mmol/l').region('SEARD').smoker().diabetic().build()
result = WHO().calculate(params)
print('--> WHO:', params['region'], ' => ', result)
print()

params = WPB().gender("M").age(60).sbp1(120).sbp2(140).chol(5.2, 'mmol/l').region('EMRD').smoker(True).diabetic(
    True).build()
result = WHO().calculate(params)
print('--> WHO:', params['region'], ' => ', result)
print()

params = WPB().gender('M').age(50).sbp1(150).sbp2(170).chol(7, 'mmol/l').region('AFRD').smoker().diabetic().build()
result = WHO().calculate(params)
print('--> WHO:', params['region'], ' => ', result)
print()

params = WPB().gender("M").age(50).sbp1(150).sbp2(170).chol(7, 'mmol/l').region('AFRE').smoker(False).diabetic().build()
result = WHO().calculate(params)
print('--> WHO:', params['region'], ' => ', result)
print()

params = WPB().gender('M').age(70).sbp1(130).sbp2(145).chol(270, 'mg/dl').smoker().diabetic().build()
result = WHO().calculate(params)
print('--> WHO:', params['region'], ' => ', result)
print()

params = WPB().gender('M').age(40).sbp1(162).sbp2(160).chol(5.2, 'mmol/L').build()
result = WHO().calculate(params)
print('--> WHO:', params, ' => ', result)
print()

input_params = {
    'request': {
        'api_key': '4325872943oeqitrqet7',
        'api_secret': '3459823jfweureitu',
        'request_api': 'https://developers.openhealthalgorithms.org/algos/hearts/',
        'country_code': 'D',
        'response_type': 'COMPLETE',
    },
    'body': {
        'region': 'SEARD',
        'last_assessment': {
            'assessment_date': '',
            'cvd_risk': '20',
        },
        'demographics': {
            'gender': 'M',
            'age': 70,
            'dob': ['computed', '01/10/1987'],
            'occupation': 'office_worker',
            'monthly_income': '',
        },
        'measurements': {
            'height': [1.5, 'm'],
            'weight': [60.0, 'kg'],
            'waist': [99.0, 'cm'],
            'hip': [104.0, 'cm'],
            'sbp': [161, 'sitting'],
            'dbp': [91, 'sitting'],
        },
        'smoking': {
            'current': 1,
            'ex_smoker': 1,
            'quit_within_year': 0,
        },
        'physical_activity': '120',
        'diet_history': {
            'fruit': 1, 'veg': 6, 'rice': 2, 'oil': 'olive',
        },
        'medical_history': {
            'conditions': ['asthma', 'tuberculosis'],
        },
        'allergies': {},
        'medications': ['anti_hypertensive', 'statin', 'antiplatelet', 'bronchodilator'],
        'family_history': ['diabetes', 'cvd'],
        'pathology': {
            'bsl': {
                'type': 'random', 'units': 'mmol/L', 'value': 5,
            },
            'cholesterol': {
                'type': 'fasting', 'units': 'mmol/L', 'total_chol': 5.2, 'hdl': 1.6, 'ldl': 2.4,
            },
        },
    },
}

print('--- HEARTS Package Demo ---\n')
result = HEARTS().calculate(input_params)
print('--> HEARTS: => ', result)
print()

with open('response_hearts.json', 'w') as fp:
    json.dump(result, fp)

print('--- General Health Assessment using FRE Demo ---\n')
result = HA().calculate(input_params)
print('--> HealthAssessment ALGO: => ', result)
print()

with open('response_healthassessment.json', 'w') as fp:
    json.dump(result, fp)

print(' --- Singapore CVD FRE demo ---\n')
params = SGFPB() \
    .gender('m') \
    .age(60) \
    .ethnicity('indian') \
    .t_chol(4.6, 'mmol/l') \
    .hdl_chol(1.8, 'mmol/l') \
    .sbp(125) \
    .smoker(True) \
    .diabetic(True) \
    .bp_medication(False) \
    .build()

result = SgFramingham().calculate(params)
print('--> Sg Framingham:', result)
print()

print('--- SingHealth Package Demo ---\n')
result = SingHealth().calculate(SingHealth.get_sample_params())
print('--> SingHealth: => ', result)
print()