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Mesothelioma’s disease data set Data Set
Download: Data Folder, Data Set Description

Abstract: 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.

Data Set Characteristics:  

Multivariate

Number of Instances:

324

Area:

Computer

Attribute Characteristics:

Real

Number of Attributes:

34

Date Donated

2016-01-11

Associated Tasks:

Classification

Missing Values?

N/A

Number of Web Hits:

15969


Source:

This data was prepared by;
Abdullah Cetin Tanrikulu from Dicle University, Faculty of Medicine, Department of Chest Diseases, 21100 Diyarbakir, Turkey
e-mail:cetintanrikulu '@' hotmail.com
Orhan Er from Bozok University, Faculty of Engineering, Department of Electrical and Electronics Eng., 66200 Yozgat, Turkey
e-mail:orhan.er@bozok.edu.tr


Data Set 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.


Attribute 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.


Relevant Papers:

An approach based on probabilistic neural network for diagnosis of Mesothelioma's disease
By: Er, Orhan; Tanrikulu, Abdullah Cetin; Abakay, Abdurrahman; et al.
COMPUTERS & ELECTRICAL ENGINEERING Volume: 38 Issue: 1 Pages: 75-81 Published: JAN 2012



Citation Request:

An approach based on probabilistic neural network for diagnosis of Mesothelioma's disease
By: Er, Orhan; Tanrikulu, Abdullah Cetin; Abakay, Abdurrahman; et al.
COMPUTERS & ELECTRICAL ENGINEERING Volume: 38 Issue: 1 Pages: 75-81 Published: JAN 2012


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