├── README.md ├── disease_predictor.py └── Testing.csv /README.md: -------------------------------------------------------------------------------- 1 | # Disease-prediction-using-Machine-Learning 2 | Implementation of various machine learning algorithms to predict the disease from symptoms given by user 3 | 4 | ### Sourcerer [![](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/images/0)](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/links/0)[![](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/images/1)](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/links/1)[![](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/images/2)](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/links/2)[![](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/images/3)](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/links/3)[![](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/images/4)](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/links/4)[![](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/images/5)](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/links/5)[![](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/images/6)](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/links/6)[![](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/images/7)](https://sourcerer.io/fame/ParthPathak27/ParthPathak27/Disease-prediction-using-Machine-Learning/links/7) 5 | -------------------------------------------------------------------------------- /disease_predictor.py: -------------------------------------------------------------------------------- 1 | from tkinter import * 2 | import numpy as np 3 | import pandas as pd 4 | # from gui_stuff import * 5 | 6 | l1=['back_pain','constipation','abdominal_pain','diarrhoea','mild_fever','yellow_urine', 7 | 'yellowing_of_eyes','acute_liver_failure','fluid_overload','swelling_of_stomach', 8 | 'swelled_lymph_nodes','malaise','blurred_and_distorted_vision','phlegm','throat_irritation', 9 | 'redness_of_eyes','sinus_pressure','runny_nose','congestion','chest_pain','weakness_in_limbs', 10 | 'fast_heart_rate','pain_during_bowel_movements','pain_in_anal_region','bloody_stool', 11 | 'irritation_in_anus','neck_pain','dizziness','cramps','bruising','obesity','swollen_legs', 12 | 'swollen_blood_vessels','puffy_face_and_eyes','enlarged_thyroid','brittle_nails', 13 | 'swollen_extremeties','excessive_hunger','extra_marital_contacts','drying_and_tingling_lips', 14 | 'slurred_speech','knee_pain','hip_joint_pain','muscle_weakness','stiff_neck','swelling_joints', 15 | 'movement_stiffness','spinning_movements','loss_of_balance','unsteadiness', 16 | 'weakness_of_one_body_side','loss_of_smell','bladder_discomfort','foul_smell_of urine', 17 | 'continuous_feel_of_urine','passage_of_gases','internal_itching','toxic_look_(typhos)', 18 | 'depression','irritability','muscle_pain','altered_sensorium','red_spots_over_body','belly_pain', 19 | 'abnormal_menstruation','dischromic _patches','watering_from_eyes','increased_appetite','polyuria','family_history','mucoid_sputum', 20 | 'rusty_sputum','lack_of_concentration','visual_disturbances','receiving_blood_transfusion', 21 | 'receiving_unsterile_injections','coma','stomach_bleeding','distention_of_abdomen', 22 | 'history_of_alcohol_consumption','fluid_overload','blood_in_sputum','prominent_veins_on_calf', 23 | 'palpitations','painful_walking','pus_filled_pimples','blackheads','scurring','skin_peeling', 24 | 'silver_like_dusting','small_dents_in_nails','inflammatory_nails','blister','red_sore_around_nose', 25 | 'yellow_crust_ooze'] 26 | 27 | disease=['Fungal infection','Allergy','GERD','Chronic cholestasis','Drug Reaction', 28 | 'Peptic ulcer diseae','AIDS','Diabetes','Gastroenteritis','Bronchial Asthma','Hypertension', 29 | ' Migraine','Cervical spondylosis', 30 | 'Paralysis (brain hemorrhage)','Jaundice','Malaria','Chicken pox','Dengue','Typhoid','hepatitis A', 31 | 'Hepatitis B','Hepatitis C','Hepatitis D','Hepatitis E','Alcoholic hepatitis','Tuberculosis', 32 | 'Common Cold','Pneumonia','Dimorphic hemmorhoids(piles)', 33 | 'Heartattack','Varicoseveins','Hypothyroidism','Hyperthyroidism','Hypoglycemia','Osteoarthristis', 34 | 'Arthritis','(vertigo) Paroymsal Positional Vertigo','Acne','Urinary tract infection','Psoriasis', 35 | 'Impetigo'] 36 | 37 | l2=[] 38 | for x in range(0,len(l1)): 39 | l2.append(0) 40 | 41 | # TESTING DATA df ------------------------------------------------------------------------------------- 42 | df=pd.read_csv("Training.csv") 43 | 44 | df.replace({'prognosis':{'Fungal infection':0,'Allergy':1,'GERD':2,'Chronic cholestasis':3,'Drug Reaction':4, 45 | 'Peptic ulcer diseae':5,'AIDS':6,'Diabetes ':7,'Gastroenteritis':8,'Bronchial Asthma':9,'Hypertension ':10, 46 | 'Migraine':11,'Cervical spondylosis':12, 47 | 'Paralysis (brain hemorrhage)':13,'Jaundice':14,'Malaria':15,'Chicken pox':16,'Dengue':17,'Typhoid':18,'hepatitis A':19, 48 | 'Hepatitis B':20,'Hepatitis C':21,'Hepatitis D':22,'Hepatitis E':23,'Alcoholic hepatitis':24,'Tuberculosis':25, 49 | 'Common Cold':26,'Pneumonia':27,'Dimorphic hemmorhoids(piles)':28,'Heart attack':29,'Varicose veins':30,'Hypothyroidism':31, 50 | 'Hyperthyroidism':32,'Hypoglycemia':33,'Osteoarthristis':34,'Arthritis':35, 51 | '(vertigo) Paroymsal Positional Vertigo':36,'Acne':37,'Urinary tract infection':38,'Psoriasis':39, 52 | 'Impetigo':40}},inplace=True) 53 | 54 | # print(df.head()) 55 | 56 | X= df[l1] 57 | 58 | y = df[["prognosis"]] 59 | np.ravel(y) 60 | # print(y) 61 | 62 | # TRAINING DATA tr -------------------------------------------------------------------------------- 63 | tr=pd.read_csv("Testing.csv") 64 | tr.replace({'prognosis':{'Fungal infection':0,'Allergy':1,'GERD':2,'Chronic cholestasis':3,'Drug Reaction':4, 65 | 'Peptic ulcer diseae':5,'AIDS':6,'Diabetes ':7,'Gastroenteritis':8,'Bronchial Asthma':9,'Hypertension ':10, 66 | 'Migraine':11,'Cervical spondylosis':12, 67 | 'Paralysis (brain hemorrhage)':13,'Jaundice':14,'Malaria':15,'Chicken pox':16,'Dengue':17,'Typhoid':18,'hepatitis A':19, 68 | 'Hepatitis B':20,'Hepatitis C':21,'Hepatitis D':22,'Hepatitis E':23,'Alcoholic hepatitis':24,'Tuberculosis':25, 69 | 'Common Cold':26,'Pneumonia':27,'Dimorphic hemmorhoids(piles)':28,'Heart attack':29,'Varicose veins':30,'Hypothyroidism':31, 70 | 'Hyperthyroidism':32,'Hypoglycemia':33,'Osteoarthristis':34,'Arthritis':35, 71 | '(vertigo) Paroymsal Positional Vertigo':36,'Acne':37,'Urinary tract infection':38,'Psoriasis':39, 72 | 'Impetigo':40}},inplace=True) 73 | 74 | X_test= tr[l1] 75 | y_test = tr[["prognosis"]] 76 | np.ravel(y_test) 77 | # ------------------------------------------------------------------------------------------------------ 78 | 79 | def DecisionTree(): 80 | 81 | from sklearn import tree 82 | 83 | clf3 = tree.DecisionTreeClassifier() # empty model of the decision tree 84 | clf3 = clf3.fit(X,y) 85 | 86 | # calculating accuracy------------------------------------------------------------------- 87 | from sklearn.metrics import accuracy_score 88 | y_pred=clf3.predict(X_test) 89 | print(accuracy_score(y_test, y_pred)) 90 | print(accuracy_score(y_test, y_pred,normalize=False)) 91 | # ----------------------------------------------------- 92 | 93 | psymptoms = [Symptom1.get(),Symptom2.get(),Symptom3.get(),Symptom4.get(),Symptom5.get()] 94 | 95 | for k in range(0,len(l1)): 96 | # print (k,) 97 | for z in psymptoms: 98 | if(z==l1[k]): 99 | l2[k]=1 100 | 101 | inputtest = [l2] 102 | predict = clf3.predict(inputtest) 103 | predicted=predict[0] 104 | 105 | h='no' 106 | for a in range(0,len(disease)): 107 | if(predicted == a): 108 | h='yes' 109 | break 110 | 111 | 112 | if (h=='yes'): 113 | t1.delete("1.0", END) 114 | t1.insert(END, disease[a]) 115 | else: 116 | t1.delete("1.0", END) 117 | t1.insert(END, "Not Found") 118 | 119 | 120 | def randomforest(): 121 | from sklearn.ensemble import RandomForestClassifier 122 | clf4 = RandomForestClassifier() 123 | clf4 = clf4.fit(X,np.ravel(y)) 124 | 125 | # calculating accuracy------------------------------------------------------------------- 126 | from sklearn.metrics import accuracy_score 127 | y_pred=clf4.predict(X_test) 128 | print(accuracy_score(y_test, y_pred)) 129 | print(accuracy_score(y_test, y_pred,normalize=False)) 130 | # ----------------------------------------------------- 131 | 132 | psymptoms = [Symptom1.get(),Symptom2.get(),Symptom3.get(),Symptom4.get(),Symptom5.get()] 133 | 134 | for k in range(0,len(l1)): 135 | for z in psymptoms: 136 | if(z==l1[k]): 137 | l2[k]=1 138 | 139 | inputtest = [l2] 140 | predict = clf4.predict(inputtest) 141 | predicted=predict[0] 142 | 143 | h='no' 144 | for a in range(0,len(disease)): 145 | if(predicted == a): 146 | h='yes' 147 | break 148 | 149 | if (h=='yes'): 150 | t2.delete("1.0", END) 151 | t2.insert(END, disease[a]) 152 | else: 153 | t2.delete("1.0", END) 154 | t2.insert(END, "Not Found") 155 | 156 | 157 | def NaiveBayes(): 158 | from sklearn.naive_bayes import GaussianNB 159 | gnb = GaussianNB() 160 | gnb=gnb.fit(X,np.ravel(y)) 161 | 162 | # calculating accuracy------------------------------------------------------------------- 163 | from sklearn.metrics import accuracy_score 164 | y_pred=gnb.predict(X_test) 165 | print(accuracy_score(y_test, y_pred)) 166 | print(accuracy_score(y_test, y_pred,normalize=False)) 167 | # ----------------------------------------------------- 168 | 169 | psymptoms = [Symptom1.get(),Symptom2.get(),Symptom3.get(),Symptom4.get(),Symptom5.get()] 170 | for k in range(0,len(l1)): 171 | for z in psymptoms: 172 | if(z==l1[k]): 173 | l2[k]=1 174 | 175 | inputtest = [l2] 176 | predict = gnb.predict(inputtest) 177 | predicted=predict[0] 178 | 179 | h='no' 180 | for a in range(0,len(disease)): 181 | if(predicted == a): 182 | h='yes' 183 | break 184 | 185 | if (h=='yes'): 186 | t3.delete("1.0", END) 187 | t3.insert(END, disease[a]) 188 | else: 189 | t3.delete("1.0", END) 190 | t3.insert(END, "Not Found") 191 | 192 | # gui_stuff------------------------------------------------------------------------------------ 193 | 194 | root = Tk() 195 | root.configure(background='blue') 196 | 197 | # entry variables 198 | Symptom1 = StringVar() 199 | Symptom1.set(None) 200 | Symptom2 = StringVar() 201 | Symptom2.set(None) 202 | Symptom3 = StringVar() 203 | Symptom3.set(None) 204 | Symptom4 = StringVar() 205 | Symptom4.set(None) 206 | Symptom5 = StringVar() 207 | Symptom5.set(None) 208 | Name = StringVar() 209 | 210 | # Heading 211 | w2 = Label(root, justify=CENTER, text="Disease Predictor using Machine Learning", fg="white", bg="blue") 212 | w2.config(font=("Elephant", 30)) 213 | w2.grid(row=1, column=0, columnspan=2, padx=100) 214 | w2 = Label(root, justify=CENTER, text="A Project by Parth Pathak", fg="white", bg="blue") 215 | w2.config(font=("Aharoni", 30)) 216 | w2.grid(row=2, column=0, columnspan=2, padx=100) 217 | 218 | # labels 219 | NameLb = Label(root, text="Name of the Patient", fg="yellow", bg="black") 220 | NameLb.grid(row=6, column=0, pady=15, sticky=W) 221 | 222 | 223 | S1Lb = Label(root, text="Symptom 1", fg="yellow", bg="black") 224 | S1Lb.grid(row=7, column=0, pady=10, sticky=W) 225 | 226 | S2Lb = Label(root, text="Symptom 2", fg="yellow", bg="black") 227 | S2Lb.grid(row=8, column=0, pady=10, sticky=W) 228 | 229 | S3Lb = Label(root, text="Symptom 3", fg="yellow", bg="black") 230 | S3Lb.grid(row=9, column=0, pady=10, sticky=W) 231 | 232 | S4Lb = Label(root, text="Symptom 4", fg="yellow", bg="black") 233 | S4Lb.grid(row=10, column=0, pady=10, sticky=W) 234 | 235 | S5Lb = Label(root, text="Symptom 5", fg="yellow", bg="black") 236 | S5Lb.grid(row=11, column=0, pady=10, sticky=W) 237 | 238 | 239 | lrLb = Label(root, text="DecisionTree", fg="white", bg="red") 240 | lrLb.grid(row=15, column=0, pady=10,sticky=W) 241 | 242 | destreeLb = Label(root, text="RandomForest", fg="white", bg="red") 243 | destreeLb.grid(row=17, column=0, pady=10, sticky=W) 244 | 245 | ranfLb = Label(root, text="NaiveBayes", fg="white", bg="red") 246 | ranfLb.grid(row=19, column=0, pady=10, sticky=W) 247 | 248 | # entries 249 | OPTIONS = sorted(l1) 250 | 251 | NameEn = Entry(root, textvariable=Name) 252 | NameEn.grid(row=6, column=1) 253 | 254 | S1En = OptionMenu(root, Symptom1,*OPTIONS) 255 | S1En.grid(row=7, column=1) 256 | 257 | S2En = OptionMenu(root, Symptom2,*OPTIONS) 258 | S2En.grid(row=8, column=1) 259 | 260 | S3En = OptionMenu(root, Symptom3,*OPTIONS) 261 | S3En.grid(row=9, column=1) 262 | 263 | S4En = OptionMenu(root, Symptom4,*OPTIONS) 264 | S4En.grid(row=10, column=1) 265 | 266 | S5En = OptionMenu(root, Symptom5,*OPTIONS) 267 | S5En.grid(row=11, column=1) 268 | 269 | 270 | dst = Button(root, text="DecisionTree", command=DecisionTree,bg="green",fg="yellow") 271 | dst.grid(row=8, column=3) 272 | 273 | rnf = Button(root, text="Randomforest", command=randomforest,bg="green",fg="yellow") 274 | rnf.grid(row=9, column=3,padx=10) 275 | 276 | lr = Button(root, text="NaiveBayes", command=NaiveBayes,bg="green",fg="yellow") 277 | lr.grid(row=10, column=3,padx=10) 278 | 279 | #textfileds 280 | t1 = Text(root, height=1, width=40,bg="orange",fg="black") 281 | t1.grid(row=15, column=1, padx=10) 282 | 283 | t2 = Text(root, height=1, width=40,bg="orange",fg="black") 284 | t2.grid(row=17, column=1 , padx=10) 285 | 286 | t3 = Text(root, height=1, width=40,bg="orange",fg="black") 287 | t3.grid(row=19, column=1 , padx=10) 288 | 289 | root.mainloop() 290 | -------------------------------------------------------------------------------- /Testing.csv: -------------------------------------------------------------------------------- 1 | itching,skin_rash,nodal_skin_eruptions,continuous_sneezing,shivering,chills,joint_pain,stomach_pain,acidity,ulcers_on_tongue,muscle_wasting,vomiting,burning_micturition,spotting_ urination,fatigue,weight_gain,anxiety,cold_hands_and_feets,mood_swings,weight_loss,restlessness,lethargy,patches_in_throat,irregular_sugar_level,cough,high_fever,sunken_eyes,breathlessness,sweating,dehydration,indigestion,headache,yellowish_skin,dark_urine,nausea,loss_of_appetite,pain_behind_the_eyes,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,prognosis 2 | 1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Fungal infection 3 | 0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Allergy 4 | 0,0,0,0,0,0,0,1,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,GERD 5 | 1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Chronic cholestasis 6 | 1,1,0,0,0,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Drug Reaction 7 | 0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Peptic ulcer diseae 8 | 0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,AIDS 9 | 0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Diabetes 10 | 0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Gastroenteritis 11 | 0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Bronchial Asthma 12 | 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Hypertension 13 | 0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Migraine 14 | 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Cervical spondylosis 15 | 0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Paralysis (brain hemorrhage) 16 | 1,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Jaundice 17 | 0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Malaria 18 | 1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Chicken pox 19 | 0,1,0,0,0,1,1,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Dengue 20 | 0,0,0,0,0,1,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,1,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Typhoid 21 | 0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,1,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,hepatitis A 22 | 1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,0,1,0,0,0,1,0,0,1,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Hepatitis B 23 | 0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Hepatitis C 24 | 0,0,0,0,0,0,1,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Hepatitis D 25 | 0,0,0,0,0,0,1,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,1,1,0,0,0,1,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Hepatitis E 26 | 0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Alcoholic hepatitis 27 | 0,0,0,0,0,1,0,0,0,0,0,1,0,0,1,0,0,0,0,1,0,0,0,0,1,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,1,0,0,0,1,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,Tuberculosis 28 | 0,0,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Common Cold 29 | 0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Pneumonia 30 | 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Dimorphic hemmorhoids(piles) 31 | 0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Heart attack 32 | 0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,Varicose veins 33 | 0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Hypothyroidism 34 | 0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Hyperthyroidism 35 | 0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,Hypoglycemia 36 | 0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,Osteoarthristis 37 | 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,Arthritis 38 | 0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,(vertigo) Paroymsal Positional Vertigo 39 | 0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,Acne 40 | 0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,Urinary tract infection 41 | 0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,Psoriasis 42 | 0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,Impetigo 43 | --------------------------------------------------------------------------------