About the data

The dataset is Electronic Health Record Predicting collected from a private Hospital in Indonesia. It contains the patient's laboratory test results used to determine next patient treatment whether in care or out care.

Attribute Information

Given is the attribute name, attribute type, the measurement unit and a brief description.

Name / Data Type / Value Sample/ Description

-----------------------------

HAEMATOCRIT /Continuous /35.1 / Patient laboratory test result of haematocrit

HAEMOGLOBINS/Continuous/11.8 / Patient laboratory test result of haemoglobins

ERYTHROCYTE/Continuous/4.65 / Patient laboratory test result of erythrocyte

LEUCOCYTE /Continuous /6.3 / Patient laboratory test result of leucocyte

THROMBOCYTE/Continuous/310/ Patient laboratory test result of thrombocyte

MCH/Continuous /25.4/ Patient laboratory test result of MCH

MCHC/Continuous/33.6/ Patient laboratory test result of MCHC

MCV/Continuous /75.5/ Patient laboratory test result of MCV

AGE/Continuous/12/ Patient age

SEX/Nominal – Binary/F/ Patient gender

SOURCE/Nominal/ {1,0}/The class target 1.= in care patient, 0 = out care patient

To load the training data in your jupyter notebook, use the below command:

import pandas as pd

patient_data = pd.read_csv("https://raw.githubusercontent.com/dphi-official/Datasets/master/patient_treat_class/training_set_label.csv" )

Saving Prediction File & Sample Submission

You can find more details on how to save a prediction file here: https://discuss.dphi.tech/t/how-to-submit-predictions/548

Sample submission: You should submit a CSV file with a header row and the sample submission can be found below.

prediction

1

0

0

1

1

Etc.

Note that the header name should be prediction else it will throw an evaluation error. A sample submission file can be found here

Test Dataset

Load the test data (name it as test_data). You can load the data using the below command.

test_data = pd.read_csv('https://raw.githubusercontent.com/dphi-official/Datasets/master/patient_treat_class/testing_set_label.csv')

Here, the target column is deliberately not there as you need to predict it

Acknowledgement

This dataset was downloaded from Mendeley Data.

Sadikin, Mujiono (2020), “EHR Dataset for Patient Treatment Classification”, Mendeley Data, V1, doi: 10.17632/7kv3rctx7m.1

Data Sprint #14: Patient Treatment Classification

Challenge Starts

Registration Ends

Challenge Ends