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# -*- coding: utf-8 -*-
"""
Created on Sun May 22 11:53:51 2022
@author: siddhardhan
"""
import pickle
import streamlit as st
from streamlit_option_menu import option_menu
# loading the saved models
diabetes_model = pickle.load(open('C:/Users/siddhardhan/Desktop/Multiple Disease Prediction System/saved models/diabetes_model.sav', 'rb'))
heart_disease_model = pickle.load(open('C:/Users/siddhardhan/Desktop/Multiple Disease Prediction System/saved models/heart_disease_model.sav','rb'))
parkinsons_model = pickle.load(open('C:/Users/siddhardhan/Desktop/Multiple Disease Prediction System/saved models/parkinsons_model.sav', 'rb'))
# sidebar for navigation
with st.sidebar:
selected = option_menu('Multiple Disease Prediction System',
['Diabetes Prediction',
'Heart Disease Prediction',
'Parkinsons Prediction'],
icons=['activity','heart','person'],
default_index=0)
# Diabetes Prediction Page
if (selected == 'Diabetes Prediction'):
# page title
st.title('Diabetes Prediction using ML')
# getting the input data from the user
col1, col2, col3 = st.columns(3)
with col1:
Pregnancies = st.text_input('Number of Pregnancies')
with col2:
Glucose = st.text_input('Glucose Level')
with col3:
BloodPressure = st.text_input('Blood Pressure value')
with col1:
SkinThickness = st.text_input('Skin Thickness value')
with col2:
Insulin = st.text_input('Insulin Level')
with col3:
BMI = st.text_input('BMI value')
with col1:
DiabetesPedigreeFunction = st.text_input('Diabetes Pedigree Function value')
with col2:
Age = st.text_input('Age of the Person')
# code for Prediction
diab_diagnosis = ''
# creating a button for Prediction
if st.button('Diabetes Test Result'):
diab_prediction = diabetes_model.predict([[Pregnancies, Glucose, BloodPressure, SkinThickness, Insulin, BMI, DiabetesPedigreeFunction, Age]])
if (diab_prediction[0] == 1):
diab_diagnosis = 'The person is diabetic'
else:
diab_diagnosis = 'The person is not diabetic'
st.success(diab_diagnosis)
# Heart Disease Prediction Page
if (selected == 'Heart Disease Prediction'):
# page title
st.title('Heart Disease Prediction using ML')
col1, col2, col3 = st.columns(3)
with col1:
age = st.text_input('Age')
with col2:
sex = st.text_input('Sex')
with col3:
cp = st.text_input('Chest Pain types')
with col1:
trestbps = st.text_input('Resting Blood Pressure')
with col2:
chol = st.text_input('Serum Cholestoral in mg/dl')
with col3:
fbs = st.text_input('Fasting Blood Sugar > 120 mg/dl')
with col1:
restecg = st.text_input('Resting Electrocardiographic results')
with col2:
thalach = st.text_input('Maximum Heart Rate achieved')
with col3:
exang = st.text_input('Exercise Induced Angina')
with col1:
oldpeak = st.text_input('ST depression induced by exercise')
with col2:
slope = st.text_input('Slope of the peak exercise ST segment')
with col3:
ca = st.text_input('Major vessels colored by flourosopy')
with col1:
thal = st.text_input('thal: 0 = normal; 1 = fixed defect; 2 = reversable defect')
# code for Prediction
heart_diagnosis = ''
# creating a button for Prediction
if st.button('Heart Disease Test Result'):
heart_prediction = heart_disease_model.predict([[age, sex, cp, trestbps, chol, fbs, restecg,thalach,exang,oldpeak,slope,ca,thal]])
if (heart_prediction[0] == 1):
heart_diagnosis = 'The person is having heart disease'
else:
heart_diagnosis = 'The person does not have any heart disease'
st.success(heart_diagnosis)
# Parkinson's Prediction Page
if (selected == "Parkinsons Prediction"):
# page title
st.title("Parkinson's Disease Prediction using ML")
col1, col2, col3, col4, col5 = st.columns(5)
with col1:
fo = st.text_input('MDVP:Fo(Hz)')
with col2:
fhi = st.text_input('MDVP:Fhi(Hz)')
with col3:
flo = st.text_input('MDVP:Flo(Hz)')
with col4:
Jitter_percent = st.text_input('MDVP:Jitter(%)')
with col5:
Jitter_Abs = st.text_input('MDVP:Jitter(Abs)')
with col1:
RAP = st.text_input('MDVP:RAP')
with col2:
PPQ = st.text_input('MDVP:PPQ')
with col3:
DDP = st.text_input('Jitter:DDP')
with col4:
Shimmer = st.text_input('MDVP:Shimmer')
with col5:
Shimmer_dB = st.text_input('MDVP:Shimmer(dB)')
with col1:
APQ3 = st.text_input('Shimmer:APQ3')
with col2:
APQ5 = st.text_input('Shimmer:APQ5')
with col3:
APQ = st.text_input('MDVP:APQ')
with col4:
DDA = st.text_input('Shimmer:DDA')
with col5:
NHR = st.text_input('NHR')
with col1:
HNR = st.text_input('HNR')
with col2:
RPDE = st.text_input('RPDE')
with col3:
DFA = st.text_input('DFA')
with col4:
spread1 = st.text_input('spread1')
with col5:
spread2 = st.text_input('spread2')
with col1:
D2 = st.text_input('D2')
with col2:
PPE = st.text_input('PPE')
# code for Prediction
parkinsons_diagnosis = ''
# creating a button for Prediction
if st.button("Parkinson's Test Result"):
parkinsons_prediction = parkinsons_model.predict([[fo, fhi, flo, Jitter_percent, Jitter_Abs, RAP, PPQ,DDP,Shimmer,Shimmer_dB,APQ3,APQ5,APQ,DDA,NHR,HNR,RPDE,DFA,spread1,spread2,D2,PPE]])
if (parkinsons_prediction[0] == 1):
parkinsons_diagnosis = "The person has Parkinson's disease"
else:
parkinsons_diagnosis = "The person does not have Parkinson's disease"
st.success(parkinsons_diagnosis)
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