Exasens
Donated on 4/21/2020
This repository introduces a novel dataset for the classification of 4 groups of respiratory diseases: Chronic Obstructive Pulmonary Disease (COPD), asthma, infected, and Healthy Controls (HC).
Dataset Characteristics
Multivariate
Subject Area
Health and Medicine
Associated Tasks
Classification, Clustering
Feature Type
Integer
# Instances
399
# Features
4
Dataset Information
Additional Information
The Exasens dataset includes demographic information on 4 groups of saliva samples (COPD-Asthma-Infected-HC) collected in the frame of a joint research project, Exasens (https://www.leibniz-healthtech.de/en/research/projects/bmbf-project-exasens/), at the Research Center Borstel, BioMaterialBank Nord (Borstel, Germany). The sampling procedure of the patient materials was approved by the local ethics committee of the University of Luebeck under the approval number AZ-16-167 and a written informed consent was obtained from all subjects. A permittivity biosensor, developed at IHP Microelectronics (Frankfurt Oder, Germany), was used for the dielectric characterization of the saliva samples for classification purposes (https://doi.org/10.3390/healthcare7010011). Definition of 4 sample groups included within the Exasens dataset: (I) Outpatients and hospitalized patients with COPD without acute respiratory infection (COPD). (II) Outpatients and hospitalized patients with asthma without acute respiratory infections (Asthma). (III) Patients with respiratory infections, but without COPD or asthma (Infected). (IV) Healthy controls without COPD, asthma, or any respiratory infection (HC).
Has Missing Values?
Yes
Variable Information
1- Diagnosis (COPD-HC-Asthma-Infected) 2- ID 3- Age 4- Gender (1=male, 0=female) 5- Smoking Status (1=Non-smoker, 2=Ex-smoker, 3=Active-smoker) 6- Saliva Permittivity: a) Imaginary part (Min(Δ)=Absolute minimum value, Avg.(Δ)=Average) b) Real part (Min(Δ)=Absolute minimum value, Avg.(Δ)=Average)
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset exasens = fetch_ucirepo(id=523) # data (as pandas dataframes) X = exasens.data.features y = exasens.data.targets # metadata print(exasens.metadata) # variable information print(exasens.variables)
Exasens. (2020). UCI Machine Learning Repository. https://doi.org/10.24432/C5M03M.
@misc{misc_exasens_523,
title = {{Exasens}},
year = {2020},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5M03M}
}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.