Abstract

This Data set was obtained from a Hospital in Karaikudi, Tamilnadu Iindia, and has 400 insstances with 25 attributes, intended for classification problems.
The Data Set has medical relevant variables that can be associated to the presence of CKD (Chronical Kidney Diasease). Some of the variables can be arguably more relevant for the model, and after analysis some of them can be correlated, so it's recommended to analyze the dataset and decide the best approach based on individual needs.
One of the attributes is a binary result that tells you if the patient actually developed the condition or not.

Therefore this data set helps to train supervised algorithms.
The data set has a small percentage of missing values, which people can decide to fill out with either median values, or leave them blank to allow the algorithm learn without noise data.

Instructions:

Data Set Information:

We use the following representation to collect the dataset
age - age
bp - blood pressure
sg - specific gravity
al - albumin
su - sugar
rbc - red blood cells
pc - pus cell
pcc - pus cell clumps
ba - bacteria
bgr - blood glucose random
bu - blood urea
sc - serum creatinine
sod - sodium
pot - potassium
hemo - hemoglobin
pcv - packed cell volume
wc - white blood cell count
rc - red blood cell count
htn - hypertension
dm - diabetes mellitus
cad - coronary artery disease
appet - appetite
pe - pedal edema
ane - anemia
class - class

Attribute Information:

We use 24 + class = 25 ( 11 numeric ,14 nominal)
1.Age(numerical)
age in years
2.Blood Pressure(numerical)
bp in mm/Hg
3.Specific Gravity(nominal)
sg - (1.005,1.010,1.015,1.020,1.025)
4.Albumin(nominal)
al - (0,1,2,3,4,5)
5.Sugar(nominal)
su - (0,1,2,3,4,5)
6.Red Blood Cells(nominal)
rbc - (normal,abnormal)
7.Pus Cell (nominal)
pc - (normal,abnormal)
8.Pus Cell clumps(nominal)
pcc - (present,notpresent)
9.Bacteria(nominal)
ba - (present,notpresent)
10.Blood Glucose Random(numerical)
bgr in mgs/dl
11.Blood Urea(numerical)
bu in mgs/dl
12.Serum Creatinine(numerical)
sc in mgs/dl
13.Sodium(numerical)
sod in mEq/L
14.Potassium(numerical)
pot in mEq/L
15.Hemoglobin(numerical)
hemo in gms
16.Packed Cell Volume(numerical)
17.White Blood Cell Count(numerical)
wc in cells/cumm
18.Red Blood Cell Count(numerical)
rc in millions/cmm
19.Hypertension(nominal)
htn - (yes,no)
20.Diabetes Mellitus(nominal)
dm - (yes,no)
21.Coronary Artery Disease(nominal)
cad - (yes,no)
22.Appetite(nominal)
appet - (good,poor)
23.Pedal Edema(nominal)
pe - (yes,no)
24.Anemia(nominal)
ane - (yes,no)
25.Class (nominal)
class - (ckd,notckd)

Comments

For research project use.

Submitted by Jerry Fuh on Fri, 11/01/2024 - 06:33

Also for case study using the DICOM format file to try machine learning methods.

Submitted by Jerry Fuh on Fri, 11/01/2024 - 06:34

Not for commercila use!