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| # -*- coding: utf-8 -*- | |
| """ | |
| Created on Tue Jan 3 18:57:20 2023 | |
| @author: pauli | |
| """ | |
| import pandas as pd | |
| import pickle | |
| from sklearn.model_selection import train_test_split | |
| from sklearn.svm import SVC | |
| from imblearn.over_sampling import SMOTE | |
| import gradio as gr | |
| import datasets | |
| def make_prediction(age,serum_creatinine,ejection_fraction): | |
| with open("model.pkl", "rb") as f: | |
| svc = pickle.load(f) | |
| preds = svc.predict([[age,serum_creatinine,ejection_fraction]]) | |
| if preds == 1: | |
| return "Patient is at high risk of dying from heart failure" | |
| return "Patient is at low risk of dying from heart failure" | |
| age_input = gr.Number(label = "Enter the age of the patient") | |
| #anaemia_input = gr.Radio(["No Anaemia","Anaemia is Present"], type = "index", label ="Does patient have Anaemia?") | |
| #dm_input = gr.Radio(["No DM","DM is Present"], type = "index",label = "Does patient have Diabetes Mellitus (DM)?") | |
| #cpk_input = gr.Number (label = "Enter level of CPK enzyme (mcg)") | |
| cr_input = gr.Number(label = "Enter level of serum creatinine (mg)") | |
| ef_input = gr.Number(label = "Enter ejection fraction (%)") | |
| output = gr.Textbox(label= "Heart Failure Risk:", lines= 3) | |
| output.style(height='30', rounded= True) | |
| with gr.Blocks(css = ".gradio-container {background-color: #10217d} #md {width: 150%} ") as demo: | |
| gr.Markdown(value= """ | |
| # **<span style="color:white">Heart Failure Predictor</span>** | |
| """, elem_id="md") | |
| gr.Interface(make_prediction, inputs=[age_input,cr_input,ef_input], | |
| outputs=output, flagging_options=["clinical suspicion is high for heart failure but model says otherwise", | |
| "clinical suspicion is low for heart failure but model says otherwise"]) | |
| #css = " div {background-color: red}", | |
| #title = "Heart Failure Predictor") | |
| gr.Markdown(""" | |
| ## <span style="color:#d7baad">Input Examples</span> | |
| <span style="color:#d7baad">Click on the examples below for a demo of how the app runs.</span> | |
| """) | |
| gr.Examples( | |
| [[49, 1, 30], [65,2.7,30]], | |
| [age_input,cr_input,ef_input], output, | |
| make_prediction, | |
| cache_examples=True) | |
| demo.launch() | |
| # | |
| # app = gr.Interface(make_prediction, inputs=[age_input,anaemia_input,cpk_input, dm_input, | |
| # cr_input,ef_input], | |
| # outputs=output, flagging_options=["clinical suspicion is high for heart failure but model says otherwise", | |
| # "clinical suspicion is low for heart failure but model says otherwise"], | |
| # title = "Heart Failure Predictor", | |
| # css="div {background-color: red}") | |
| # app.launch() |