Mesothelioma's disease data set

Donated on 1/10/2016

Mesothelioma’s disease data set were prepared at Dicle University Faculty of Medicine in Turkey. Three hundred and twenty-four Mesothelioma patient data. In the dataset, all samples have 34 features.

Dataset Characteristics

Multivariate

Subject Area

Computer Science

Associated Tasks

Classification

Feature Type

Real

# Instances

324

# Features

-

Dataset Information

Additional Information

Malignant mesotheliomas (MM) are very aggressive tumors of the pleura. These tumors are connected to asbestos exposure, however it may also be related to previous simian virus 40 (SV40) infection and quite possible for genetic predisposition. Molecular mechanisms can also be implicated in the development of mesothelioma. Rural living is associated with the development of mesothelioma. Soil mixtures containing asbestos, known as ‘white-soil’ or ‘corak’ can be found in Anatolia, Turkey and ‘Luto’ in Greece. Mesothelioma’s disease data set were prepared at Dicle University Faculty of Medicine in Turkey. Three hundred and twenty-four Mesothelioma patient data. In the dataset, all samples have 34 features.

Has Missing Values?

No

Variables Table

Variable NameRoleTypeDescriptionUnitsMissing Values
no
no
no
no
no
no
no
no
no
no

0 to 10 of 34

Additional Variable Information

The features are; age, gender, city, asbestos exposure, type of MM, duration of asbestos exposure, diagnosis method, keep side, cytology, duration of symptoms, dyspnoea, ache on chest, weakness, habit of cigarette, performance status, White Blood cell count (WBC), hemoglobin (HGB), platelet count (PLT), sedimentation, blood lactic dehydrogenise (LDH), Alkaline phosphatise (ALP), total protein, albumin, glucose, pleural lactic dehydrogenise, pleural protein, pleural albumin, pleural glucose, dead or not, pleural effusion, pleural thickness on tomography, pleural level of acidity (pH), C-reactive protein (CRP), class of diagnosis.

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Download
Install the ucimlrepo package 
pip install ucimlrepo
Import the dataset into your code 
from ucimlrepo import fetch_ucirepo 
  
# fetch dataset 
mesothelioma_s_disease_data_set = fetch_ucirepo(id=351) 
  
# data (as pandas dataframes) 
X = mesothelioma_s_disease_data_set.data.features 
y = mesothelioma_s_disease_data_set.data.targets 
  
# metadata 
print(mesothelioma_s_disease_data_set.metadata) 
  
# variable information 
print(mesothelioma_s_disease_data_set.variables)
View the full documentation
0 citations
3102 views
Citation 
Tanrikulu,Abdullah and Er,Orhan. (2016). Mesothelioma's disease data set . UCI Machine Learning Repository. https://doi.org/10.24432/C5903T.
BibTeX 
@misc{misc_mesothelioma's_disease_data_set__351,
  author       = {Tanrikulu,Abdullah and Er,Orhan},
  title        = {{Mesothelioma's disease data set }},
  year         = {2016},
  howpublished = {UCI Machine Learning Repository},
  note         = {{DOI}: https://doi.org/10.24432/C5903T}
}

Creators

Abdullah Tanrikulu

Orhan Er

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.

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