dermatology
type: Item
instance of: data set
OpenML dataset ID: 35
dataset version identifier: 1
description: 1. Title: Dermatology Database\N\N2. Source Information:\N (a) Original owners:\N -- 1. Nilsel Ilter, M.D., Ph.D., \N Gazi University, \N School of Medicine\N 06510 Ankara, Turkey\N Phone: +90 (312) 214 1080\N\N -- 2. H. Altay Guvenir, PhD., \N Bilkent University,\N Department of Computer Engineering and Information Science,\N 06533 Ankara, Turkey\N Phone: +90 (312) 266 4133\N Email: guvenir@cs.bilkent.edu.tr\N\N (b) Donor: H. Altay Guvenir,\N Bilkent University,\N Department of Computer Engineering and Information Science,\N 06533 Ankara, Turkey\N Phone: +90 (312) 266 4133\N Email: guvenir@cs.bilkent.edu.tr\N\N (c) Date: January, 1998\N\N3. Past Usage:\N 1. G. Demiroz, H. A. Govenir, and N. Ilter, \N "Learning Differential Diagnosis of Eryhemato-Squamous Diseases using\N Voting Feature Intervals", Aritificial Intelligence in Medicine,\N\N The aim is to determine the type of Eryhemato-Squamous Disease.\N\N4. Relevant Information:\N This database contains 34 attributes, 33 of which are linear\N valued and one of them is nominal. \N\N The differential diagnosis of erythemato-squamous diseases is a real\N problem in dermatology. They all share the clinical features of\N erythema and scaling, with very little differences. The diseases in\N this group are psoriasis, seboreic dermatitis, lichen planus, \N pityriasis rosea, cronic dermatitis, and pityriasis rubra pilaris.\N Usually a biopsy is necessary for the diagnosis but unfortunately\N these diseases share many histopathological features as\N well. Another difficulty for the differential diagnosis is that a\N disease may show the features of another disease at the beginning\N stage and may have the characteristic features at the following stages. \N Patients were first evaluated clinically with 12 features.\N Afterwards, skin samples were taken for the evaluation of 22\N histopathological features. The values of the histopathological features\N are determined by an analysis of the samples under a microscope. \N\N In t…
author name string: H. Altay Guvenir
author name string: PhD.
collection date: 1997
upload date: 2014-04-06T00:00:00Z
full work available at URL: dermatology.arff
full work available at URL: dermatology.zip
default target attribute: class
OpenML semantic tag: Medicine
citation text: G. Demiroz, H. A. Govenir, and N. Ilter, "Learning Differential Diagnosis of Eryhemato-Squamous Diseases using Voting Feature Intervals", Aritificial Intelligence in Medicine,
number of binary features: 1
number of classes: 6
number of features: 35
number of instances: 366
number of instances with missing values: 8
number of missing values: 8
number of numeric features: 1
number of symbolic features: 34
file format: ARFF
MaRDI profile type: Dataset
description: OpenML dataset with id 35