-
Notifications
You must be signed in to change notification settings - Fork 0
/
main.py
206 lines (149 loc) · 7.53 KB
/
main.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
from tkinter import *
import numpy as np
import pandas as pd
from sklearn import tree
l1=['back_pain','constipation','abdominal_pain','diarrhoea','mild_fever','yellow_urine',
'yellowing_of_eyes','acute_liver_failure','fluid_overload','swelling_of_stomach',
'swelled_lymph_nodes','malaise','blurred_and_distorted_vision','phlegm','throat_irritation',
'redness_of_eyes','sinus_pressure','runny_nose','congestion','chest_pain','weakness_in_limbs',
'fast_heart_rate','pain_during_bowel_movements','pain_in_anal_region','bloody_stool',
'irritation_in_anus','neck_pain','dizziness','cramps','bruising','obesity','swollen_legs',
'swollen_blood_vessels','puffy_face_and_eyes','enlarged_thyroid','brittle_nails',
'swollen_extremeties','excessive_hunger','extra_marital_contacts','drying_and_tingling_lips',
'slurred_speech','knee_pain','hip_joint_pain','muscle_weakness','stiff_neck','swelling_joints',
'movement_stiffness','spinning_movements','loss_of_balance','unsteadiness',
'weakness_of_one_body_side','loss_of_smell','bladder_discomfort','foul_smell_of urine',
'continuous_feel_of_urine','passage_of_gases','internal_itching','toxic_look_(typhos)',
'depression','irritability','muscle_pain','altered_sensorium','red_spots_over_body','belly_pain',
'abnormal_menstruation','dischromic _patches','watering_from_eyes','increased_appetite','polyuria','family_history','mucoid_sputum',
'rusty_sputum','lack_of_concentration','visual_disturbances','receiving_blood_transfusion',
'receiving_unsterile_injections','coma','stomach_bleeding','distention_of_abdomen',
'history_of_alcohol_consumption','fluid_overload','blood_in_sputum','prominent_veins_on_calf',
'palpitations','painful_walking','pus_filled_pimples','blackheads','scurring','skin_peeling',
'silver_like_dusting','small_dents_in_nails','inflammatory_nails','blister','red_sore_around_nose',
'yellow_crust_ooze','itching','skin_rash','nodal_skin_eruptions','irritability']
disease=['Fungal infection','Allergy','GERD','Chronic cholestasis','Drug Reaction',
'Peptic ulcer diseae','AIDS','Diabetes','Gastroenteritis','Bronchial Asthma','Hypertension',
' Migraine','Cervical spondylosis',
'Paralysis (brain hemorrhage)','Jaundice','Malaria','Chicken pox','Dengue','Typhoid','hepatitis A',
'Hepatitis B','Hepatitis C','Hepatitis D','Hepatitis E','Alcoholic hepatitis','Tuberculosis',
'Common Cold','Pneumonia','Dimorphic hemmorhoids(piles)',
'Heartattack','Varicoseveins','Hypothyroidism','Hyperthyroidism','Hypoglycemia','Osteoarthristis',
'Arthritis','(vertigo) Paroymsal Positional Vertigo','Acne','Urinary tract infection','Psoriasis',
'Impetigo']
l2=[]
for x in range(0,len(l1)):
l2.append(0)
df=pd.read_csv("Training.csv")
df.replace({'prognosis':{'Fungal infection':0,'Allergy':1,'GERD':2,'Chronic cholestasis':3,'Drug Reaction':4,
'Peptic ulcer diseae':5,'AIDS':6,'Diabetes ':7,'Gastroenteritis':8,'Bronchial Asthma':9,'Hypertension ':10,
'Migraine':11,'Cervical spondylosis':12,
'Paralysis (brain hemorrhage)':13,'Jaundice':14,'Malaria':15,'Chicken pox':16,'Dengue':17,'Typhoid':18,'hepatitis A':19,
'Hepatitis B':20,'Hepatitis C':21,'Hepatitis D':22,'Hepatitis E':23,'Alcoholic hepatitis':24,'Tuberculosis':25,
'Common Cold':26,'Pneumonia':27,'Dimorphic hemmorhoids(piles)':28,'Heart attack':29,'Varicose veins':30,'Hypothyroidism':31,
'Hyperthyroidism':32,'Hypoglycemia':33,'Osteoarthristis':34,'Arthritis':35,
'(vertigo) Paroymsal Positional Vertigo':36,'Acne':37,'Urinary tract infection':38,'Psoriasis':39,
'Impetigo':40}},inplace=True)
X= df[l1]
y = df[["prognosis"]]
np.ravel(y)
tr=pd.read_csv("Testing.csv")
tr.replace({'prognosis':{'Fungal infection':0,'Allergy':1,'GERD':2,'Chronic cholestasis':3,'Drug Reaction':4,
'Peptic ulcer diseae':5,'AIDS':6,'Diabetes ':7,'Gastroenteritis':8,'Bronchial Asthma':9,'Hypertension ':10,
'Migraine':11,'Cervical spondylosis':12,
'Paralysis (brain hemorrhage)':13,'Jaundice':14,'Malaria':15,'Chicken pox':16,'Dengue':17,'Typhoid':18,'hepatitis A':19,
'Hepatitis B':20,'Hepatitis C':21,'Hepatitis D':22,'Hepatitis E':23,'Alcoholic hepatitis':24,'Tuberculosis':25,
'Common Cold':26,'Pneumonia':27,'Dimorphic hemmorhoids(piles)':28,'Heart attack':29,'Varicose veins':30,'Hypothyroidism':31,
'Hyperthyroidism':32,'Hypoglycemia':33,'Osteoarthristis':34,'Arthritis':35,
'(vertigo) Paroymsal Positional Vertigo':36,'Acne':37,'Urinary tract infection':38,'Psoriasis':39,
'Impetigo':40}},inplace=True)
X_test= tr[l1]
y_test = tr[["prognosis"]]
np.ravel(y_test)
def randomforest():
from sklearn.ensemble import RandomForestClassifier
clf4 = RandomForestClassifier()
clf4 = clf4.fit(X,np.ravel(y))
from sklearn.metrics import accuracy_score
y_pred=clf4.predict(X_test)
t5.insert(END,accuracy_score(y_test, y_pred))
psymptoms = [Symptom1.get(),Symptom2.get(),Symptom3.get(),Symptom4.get(),Symptom5.get()]
for k in range(0,len(l1)):
for z in psymptoms:
if(z==l1[k]):
l2[k]=1
inputtest = [l2]
predict = clf4.predict(inputtest)
predicted=predict[0]
h='no'
for a in range(0,len(disease)):
if(predicted == a):
h='yes'
break
if (h=='yes'):
t2.delete("1.0", END)
t2.insert(END, disease[a])
else:
t2.delete("1.0", END)
t2.insert(END, "Not Found")
root = Tk()
root.configure(background='Grey')
# entry variables
Symptom1 = StringVar()
Symptom1.set(None)
Symptom2 = StringVar()
Symptom2.set(None)
Symptom3 = StringVar()
Symptom3.set(None)
Symptom4 = StringVar()
Symptom4.set(None)
Symptom5 = StringVar()
Symptom5.set(None)
Name = StringVar()
# Heading
w2 = Label(root, justify=LEFT, text="Disease Predictor", fg="Black", bg="Grey")
w2.config(font=("Elephant", 30))
w2.grid(row=1, column=0, columnspan=4, padx=150)
my_name= Label(root, justify=RIGHT, text="~Model by Abhilasha", fg="Black", bg="cyan")
my_name.config(font=("arial", 10))
my_name.grid(row=22, column=3, columnspan=4, padx=150)
# labels
NameLb = Label(root, text="Name of the Patient:", fg="white", bg="Sienna")
NameLb.grid(row=6, column=0, pady=15, padx=20, sticky=W)
NameLb = Label(root, text="Accuracy:", fg="white", bg="sienna")
NameLb.grid(row=7, column=2, pady=10, sticky=W)
#text field
S1Lb = Label(root, text="Symptom 1", fg="white", bg="Brown")
S1Lb.grid(row=7, column=0, pady=10, sticky=W)
S2Lb = Label(root, text="Symptom 2", fg="white", bg="brown")
S2Lb.grid(row=8, column=0, pady=10, sticky=W)
S3Lb = Label(root, text="Symptom 3", fg="white", bg="brown")
S3Lb.grid(row=9, column=0, pady=10, sticky=W)
S4Lb = Label(root, text="Symptom 4", fg="white", bg="brown")
S4Lb.grid(row=10, column=0, pady=10, sticky=W)
S5Lb = Label(root, text="Symptom 5", fg="white", bg="brown")
S5Lb.grid(row=11, column=0, pady=10, sticky=W)
destreeLb = Label(root, text="Predicted Disease:", fg="white", bg="sienna")
destreeLb.grid(row=17, column=0, pady=10, sticky=W)
# entries
OPTIONS = sorted(l1)
NameEn = Entry(root, textvariable=Name)
NameEn.grid(row=6, column=1)
S1En = OptionMenu(root, Symptom1,*OPTIONS)
S1En.grid(row=7, column=1)
S2En = OptionMenu(root, Symptom2,*OPTIONS)
S2En.grid(row=8, column=1)
S3En = OptionMenu(root, Symptom3,*OPTIONS)
S3En.grid(row=9, column=1)
S4En = OptionMenu(root, Symptom4,*OPTIONS)
S4En.grid(row=10, column=1)
S5En = OptionMenu(root, Symptom5,*OPTIONS)
S5En.grid(row=11, column=1)
rnf = Button(root, text="Predict", command=randomforest,bg="green",fg="yellow")
rnf.grid(row=9, column=3,padx=10)
#textfileds
t2 = Text(root, height=1, width=40,bg="white",fg="black")
t2.grid(row=17, column=1 , padx=10)
t5 = Text(root, height=1, width=40,bg="white",fg="black")
t5.grid(row=9, column=2 , padx=10)
root.mainloop()