-
Notifications
You must be signed in to change notification settings - Fork 0
/
app.py
249 lines (164 loc) · 8.14 KB
/
app.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
import os
import pickle
import streamlit as st
from streamlit_option_menu import option_menu
# Set page configuration
st.set_page_config(page_title = "SymptoScan",
layout = "wide",
page_icon = "🧑⚕️🔍")
# getting the working directory of the main.py
working_dir = os.path.dirname(os.path.abspath(__file__))
# loading the saved models
diabetes_model = pickle.load(open('./saved_models/diabetes_model.sav', 'rb'))
heart_disease_model = pickle.load(open('./saved_models/heart_disease_model.sav', 'rb'))
parkinsons_model = pickle.load(open('./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'],
menu_icon = 'hospital-fill',
icons = ['activity', 'heart', 'person'],
default_index = 0)
# Diabetes Prediction Page
if selected == 'Diabetes Prediction':
# page title
st.title('Diabetes Prediction')
# getting the input data from the user
col1, col2, col3, col4 = st.columns(4)
with col1:
Pregnancies = st.text_input('Number of Pregnancies', placeholder = 'Enter number of pregnancies')
with col2:
Glucose = st.text_input('Glucose Level', placeholder = 'Enter glucose level')
with col3:
BloodPressure = st.text_input('Blood Pressure value', placeholder = 'Enter blood pressure value < 100')
with col4:
SkinThickness = st.text_input('Skin Thickness value', placeholder = 'Enter skin thickness value < 50')
with col1:
Insulin = st.text_input('Insulin Level', placeholder = 'Enter insulin level')
with col2:
BMI = st.text_input('BMI value', placeholder = 'Enter BMI value')
with col3:
DiabetesPedigreeFunction = st.text_input('Diabetes Pedigree Function value', placeholder = 'Enter DPF value')
with col4:
Age = st.text_input('Age of the Person', placeholder = 'Enter patient age')
# code for Prediction
diab_diagnosis = ''
# creating a button for Prediction
if st.button('Diabetes Test Result'):
user_input = [Pregnancies, Glucose, BloodPressure, SkinThickness, Insulin,
BMI, DiabetesPedigreeFunction, Age]
user_input = [float(x) for x in user_input]
diab_prediction = diabetes_model.predict([user_input])
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')
col1, col2, col3 = st.columns(3)
with col1:
age = st.text_input('Age', placeholder = 'Enter patient age')
with col2:
sex = st.text_input('Sex', placeholder = 'Enter M for Male or F for Female')
with col3:
cp = st.text_input('Chest Pain types', placeholder = 'Enter chest pain intensity (0 to 3)')
with col1:
trestbps = st.text_input('Resting Blood Pressure', placeholder = 'Enter resting blood pressure (< 200)')
with col2:
chol = st.text_input('Serum Cholestoral', placeholder = 'Enter serum cholestrol in mg/dl')
with col3:
fbs = st.text_input('Fasting Blood Sugar', placeholder = 'Enter fasting blood sugar > 120 mg/dl')
with col1:
restecg = st.text_input('Resting Electrocardiographic results', placeholder = 'Enter resting electrocardiographic result (0 or 1)')
with col2:
thalach = st.text_input('Maximum Heart Rate achieved', placeholder = 'Enter maximum heart rate')
with col3:
exang = st.text_input('Exercise Induced Angina', placeholder = 'Enter exercise induced angina')
with col1:
oldpeak = st.text_input('ST depression induced by exercise', placeholder = 'Enter depression induces by execise')
with col2:
slope = st.text_input('Slope of the peak exercise ST segment', placeholder = 'Enter slope of peak exercise')
with col3:
ca = st.text_input('Major vessels colored by flourosopy', placeholder = 'Enter major vessels colored by flourosopy')
with col1:
thal = st.text_input('thal', placeholder = '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'):
user_input = [age, sex, cp, trestbps, chol, fbs, restecg, thalach, exang, oldpeak, slope, ca, thal]
user_input = [float(x) for x in user_input]
heart_prediction = heart_disease_model.predict([user_input])
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")
col1, col2, col3, col4, col5 = st.columns(5)
with col1:
fo = st.text_input('MDVP:Fo', placeholder = 'Enter MDVP:Fo in Hz')
with col2:
fhi = st.text_input('MDVP:Fhi', placeholder = 'Enter MDVP:Fhi in Hz')
with col3:
flo = st.text_input('MDVP:Flo', placeholder = 'Enter MDVP:Flo in Hz')
with col4:
Jitter_percent = st.text_input('MDVP:Jitter', placeholder = 'Enter MDVP:Jitter in percentage')
with col5:
Jitter_Abs = st.text_input('MDVP:Jitter', placeholder = 'Enter MDVP:Jitter in Abs')
with col1:
RAP = st.text_input('MDVP:RAP', placeholder = 'Enter MDVP:RAP')
with col2:
PPQ = st.text_input('MDVP:PPQ', placeholder = 'Enter MDVP:PPQ')
with col3:
DDP = st.text_input('Jitter:DDP', placeholder = 'Enter Jitter:DDP')
with col4:
Shimmer = st.text_input('MDVP:Shimmer', placeholder = 'Enter MDVP:Shimmer')
with col5:
Shimmer_dB = st.text_input('MDVP:Shimmer', placeholder = 'Enter MDVP:Shimmer in decibel')
with col1:
APQ3 = st.text_input('Shimmer:APQ3', placeholder = 'Enter Shimmer:APQ3')
with col2:
APQ5 = st.text_input('Shimmer:APQ5', placeholder = 'Enter Shimmer:APQ5')
with col3:
APQ = st.text_input('MDVP:APQ', placeholder = 'Enter MDVP:APQ')
with col4:
DDA = st.text_input('Shimmer:DDA', placeholder = 'Enter Shimmer:DDA')
with col5:
NHR = st.text_input('NHR', placeholder = 'Enter NHR')
with col1:
HNR = st.text_input('HNR', placeholder = 'Enter HNR')
with col2:
RPDE = st.text_input('RPDE', placeholder = 'Enter RPDE')
with col3:
DFA = st.text_input('DFA', placeholder = 'Enter DFA')
with col4:
spread1 = st.text_input('spread1', placeholder = 'Enter spread1')
with col5:
spread2 = st.text_input('spread2', placeholder = 'Enter spread2')
with col1:
D2 = st.text_input('D2', placeholder = 'Enter D2')
with col2:
PPE = st.text_input('PPE', placeholder = 'Enter PPE')
# code for Prediction
parkinsons_diagnosis = ''
# creating a button for Prediction
if st.button("Parkinson's Test Result"):
user_input = [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]
user_input = [float(x) for x in user_input]
parkinsons_prediction = parkinsons_model.predict([user_input])
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)