extention of Z-Alizadeh sani dataset
Donated on 11/16/2017
It was collected for CAD diagnosis.
Dataset Characteristics
Tabular
Subject Area
Health and Medicine
Associated Tasks
Classification
Feature Type
Integer, Real
# Instances
303
# Features
-
Dataset Information
Additional Information
Each patient could be in two possible categories CAD or Normal. A patient is categorized as CAD, if his/her diameter narrowing is greater than or equal to 50%, and otherwise as Normal . Note 1: In this extension LAD, LCX, and RCA features have been added. CAD (Last column in dataset) happens when at least one of these three arteries is stenotic. To use this dataset only one of the LAD, LCX, RCA or Cath (Result of angiography) must be in dataset and the other ones must be eliminated for classification. Note 2: This dataset not only can be used for CAD detection, but also for stenosis diagnosis of each LAD, LCX and RCA arteries.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no |
0 to 10 of 59
Additional Variable Information
The extension of Z-Alizadeh Sani dataset contains the records of 303 patients, each of which have 59 features.The features are arranged in four groups: demographic, symptom and examination, ECG, and laboratory and echo features. Note 1: In this extension LAD, LCX, and RCA features have been added. CAD (Last column in dataset) happens when at least one of these three arteries is stenotic. To use this dataset only one of the LAD, LCX, RCA or Cath (Result of angiography) must be in dataset and the other ones must be eliminated for classification. Note 2: This dataset not only can be used for CAD detection, but also for stenosis diagnosis of each LAD, LCX and RCA arteries.
Dataset Files
| File | Size |
|---|---|
| extention of Z-Alizadeh sani dataset.xlsx | 128.1 KB |
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset extention_of_z_alizadeh_sani_dataset = fetch_ucirepo(id=411) # data (as pandas dataframes) X = extention_of_z_alizadeh_sani_dataset.data.features y = extention_of_z_alizadeh_sani_dataset.data.targets # metadata print(extention_of_z_alizadeh_sani_dataset.metadata) # variable information print(extention_of_z_alizadeh_sani_dataset.variables)
Alizadehsani, R., Roshanzamir, M., & Sani, Z. (2013). extention of Z-Alizadeh sani dataset [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5461K.
Creators
Roohallah Alizadehsani
Mohamad Roshanzamir
Zahra Sani
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.