def predict_risk_mort(cols, model, features, imputer, explainer, feature_vals,
temp_unit, card_text, language):
score, imputed_text, plot = predict_risk(True, model, features, imputer,
explainer, feature_vals, cols,
temp_unit, language)
card_content = [
html.H4(card_text, className="score-calculator-card-content"),
html.H4(str(score) + "%", className="score-calculator-card-content"),
]
return card_content, imputed_text, plot
def predict_risk_mort(cols, model, features, imputer, explainer, feature_vals,
temp_unit, card_text, language):
"""Given features, other input, etc. calculate a score and return score_card, imputed_text, and user plot"""
score, imputed_text, plot = predict_risk(True, model, features, imputer,
explainer, feature_vals, cols,
temp_unit, language)
card_content = [
html.H4(card_text, className="score-calculator-card-content"),
html.H4(str(score) + "%", className="score-calculator-card-content"),
]
return card_content, imputed_text, plot
def predict_risk_infec(cols, model, features, imputer, explainer, feature_vals,
temp_unit, card_text, language):
score, impute_text, plot = predict_risk(False, model, features, imputer,
explainer, feature_vals, cols,
temp_unit, language)
card_content = [
html.H4(card_text[0],
className="score-calculator-card-content-infection"),
html.H4(str(int(math.floor(score / 10.0))) + card_text[1],
className="score-calculator-card-content-infection"),
]
return card_content, impute_text, plot
def predict_risk_mort(labs, feature_vals, temp_unit, card_text, language):
if labs:
cols = cols_labs_mort
model = labs_model_mort
features = labs_features_mort
imputer = labs_imputer_mort
explainer = labs_explainer_mort
else:
cols = cols_no_labs_mort
model = no_labs_model_mort
features = no_labs_features_mort
imputer = no_labs_imputer_mort
explainer = no_labs_explainer_mort
score, imputed_text, plot = predict_risk(True, model, features, imputer,
explainer, feature_vals, cols,
temp_unit, labs, language)
card_content = [
html.H4(card_text, className="score-calculator-card-content"),
html.H4(str(score) + "%", className="score-calculator-card-content"),
]
return card_content, imputed_text, plot
def predict_risk_infec(labs, feature_vals, temp_unit, card_text, language):
if labs:
with open('assets/risk_calculators/infection/labs_imputer.pkl',
'rb') as file:
imputer_pickle = pickle.load(file)
with open('assets/risk_calculators/infection/labs_json.pkl',
'rb') as file:
features_pickle = pickle.load(file)
with open('assets/risk_calculators/infection/labs_model_explainer.pkl',
'rb') as file:
model_pickle = pickle.load(file)
cols = get_cols(True)
else:
with open('assets/risk_calculators/infection/without_labs_imputer.pkl',
'rb') as file:
imputer_pickle = pickle.load(file)
with open('assets/risk_calculators/infection/without_labs_json.pkl',
'rb') as file:
features_pickle = pickle.load(file)
with open(
'assets/risk_calculators/infection/without_labs_model_explainer.pkl',
'rb') as file:
model_pickle = pickle.load(file)
cols = get_cols(False)
model = model_pickle["model"]
features = features_pickle["json"]
imputer = imputer_pickle["imputer"]
explainer = model_pickle["explainer"]
score, impute_text, plot = predict_risk(False, model, features, imputer,
explainer, feature_vals, cols,
temp_unit, labs, language)
card_content = [
html.H4(card_text[0],
className="score-calculator-card-content-infection"),
html.H4(str(int(math.floor(score / 10.0))) + card_text[1],
className="score-calculator-card-content-infection"),
]
return card_content, impute_text, plot
def predict_risk_mort(labs, feature_vals, temp_unit, card_text, language):
if labs:
with open('assets/risk_calculators/mortality/labs_imputer.pkl',
'rb') as file:
imputer_pickle = pickle.load(file)
with open('assets/risk_calculators/mortality/labs_json.pkl',
'rb') as file:
features_pickle = pickle.load(file)
with open('assets/risk_calculators/mortality/labs_model_explainer.pkl',
'rb') as file:
model_pickle = pickle.load(file)
cols = get_cols(True)
else:
with open('assets/risk_calculators/mortality/without_labs_imputer.pkl',
'rb') as file:
imputer_pickle = pickle.load(file)
with open('assets/risk_calculators/mortality/without_labs_json.pkl',
'rb') as file:
features_pickle = pickle.load(file)
with open(
'assets/risk_calculators/mortality/without_labs_model_explainer.pkl',
'rb') as file:
model_pickle = pickle.load(file)
cols = get_cols(False)
model = model_pickle["model"]
features = features_pickle["json"]
imputer = imputer_pickle["imputer"]
explainer = model_pickle["explainer"]
score, imputed_text, plot = predict_risk(True, model, features, imputer,
explainer, feature_vals, cols,
temp_unit, labs, language)
card_content = [
html.H4(card_text, className="score-calculator-card-content"),
html.H4(str(score) + "%", className="score-calculator-card-content"),
]
return card_content, imputed_text, plot
def predict_risk_infec(labs, feature_vals, temp_unit, card_text, language):
if labs:
cols = cols_labs_infec
model = labs_model_infec
features = labs_features_infec
imputer = labs_imputer_infec
explainer = labs_explainer_infec
else:
cols = cols_no_labs_infec
model = no_labs_model_infec
features = no_labs_features_infec
imputer = no_labs_imputer_infec
explainer = no_labs_explainer_infec
score, impute_text, plot = predict_risk(False, model, features, imputer,
explainer, feature_vals, cols,
temp_unit, labs, language)
card_content = [
html.H4(card_text[0],
className="score-calculator-card-content-infection"),
html.H4(str(int(math.floor(score / 10.0))) + card_text[1],
className="score-calculator-card-content-infection"),
]
return card_content, impute_text, plot