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Caesarian Section Classification Dataset Data Set
Download: Data Folder, Data Set Description

Abstract: This dataset contains information about caesarian section results of 80 pregnant women with the most important characteristics of delivery problems in the medical field.

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Name: Muhammad Zain Amin
Email: ZainAmin1 '@'
Institution: University of Engineering and Technology, Lahore, Pakistan

Name: Amir Ali
Email: amirali.ryk1 '@'
Institution: University of Engineering and Technology, Lahore, Pakistan

Data Set Information:

Provide all relevant information about your data set.

Attribute Information:

We choose age, delivery number, delivery time, blood pressure and heart status.
We classify delivery time to Premature, Timely and Latecomer. As like the delivery time we consider blood pressure in three statuses of Low, Normal and High moods. Heart Problem is classified as apt and inept.

@attribute 'Age' { 22,26,28,27,32,36,33,23,20,29,25,37,24,18,30,40,31,19,21,35,17,38 }
@attribute 'Delivery number' { 1,2,3,4 }
@attribute 'Delivery time' { 0,1,2 } -> {0 = timely , 1 = premature , 2 = latecomer}
@attribute 'Blood of Pressure' { 2,1,0 } -> {0 = low , 1 = normal , 2 = high }
@attribute 'Heart Problem' { 1,0 } -> {0 = apt, 1 = inept }

@attribute Caesarian { 0,1 } -> {0 = No, 1 = Yes }

Relevant Papers:

1. M.Zain Amin, Amir Ali.'Performance Evaluation of Supervised Machine Learning Classifiers for Predicting Healthcare Operational Decisions'.Machine Learning for Operational Decision Making, Wavy Artificial Intelligence Research Foundation, Pakistan, 2018

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