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皮肤科数据集,包含红斑和鳞状疾病诊断数据

皮肤科数据集,包含红斑和鳞状疾病诊断数据

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Medical Classification

Data Set Information:This database contains 34 attributes, 33 of which are linear valued and one of them is nominal. The......

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    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    Data Set Information:

    This database contains 34 attributes, 33 of which are linear valued and one of them is nominal.

    The differential diagnosis of erythemato-squamous diseases is a real problem in dermatology. They all share the clinical features of erythema and scaling, with very little differences. The diseases in this group are psoriasis, seboreic dermatitis, lichen planus, pityriasis rosea, cronic dermatitis, and pityriasis rubra pilaris. Usually a biopsy is necessary for the diagnosis but unfortunately these diseases share many histopathological features as well. Another difficulty for the differential diagnosis is that a disease may show the features of another disease at the beginning stage and may have the characteristic features at the following stages. Patients were first evaluated clinically with 12 features. Afterwards, skin samples were taken for the evaluation of 22 histopathological features. The values of the histopathological features are determined by an analysis of the samples under a microscope.

    In the dataset constructed for this domain, the family history feature has the value 1 if any of these diseases has been observed in the family, and 0 otherwise. The age feature simply represents the age of the patient. Every other feature (clinical and histopathological) was given a degree in the range of 0 to 3. Here, 0 indicates that the feature was not present, 3 indicates the largest amount possible, and 1, 2 indicate the relative intermediate values.

    The names and id numbers of the patients were recently removed from the database.


    Attribute Information:

    Clinical Attributes: (take values 0, 1, 2, 3, unless otherwise indicated)
         1: erythema
         2: scaling
         3: definite borders
         4: itching
         5: koebner phenomenon
         6: polygonal papules
         7: follicular papules
         8: oral mucosal involvement
         9: knee and elbow involvement
        10: scalp involvement
        11: family history, (0 or 1)
        34: Age (linear)

        Histopathological Attributes: (take values 0, 1, 2, 3)
        12: melanin incontinence
        13: eosinophils in the infiltrate
        14: PNL infiltrate
        15: fibrosis of the papillary dermis
        16: exocytosis
        17: acanthosis
        18: hyperkeratosis
        19: parakeratosis
        20: clubbing of the rete ridges
        21: elongation of the rete ridges
        22: thinning of the suprapapillary epidermis
        23: spongiform pustule
        24: munro microabcess
        25: focal hypergranulosis
        26: disappearance of the granular layer
        27: vacuolisation and damage of basal layer
        28: spongiosis
        29: saw-tooth appearance of retes
        30: follicular horn plug
        31: perifollicular parakeratosis
        32: inflammatory monoluclear inflitrate
        33: band-like infiltrate


    Relevant Papers:

    G. Demiroz, H. A. Govenir, and N. Ilter, "Learning Differential Diagnosis of Eryhemato-Squamous Diseases using Voting Feature Intervals", Aritificial Intelligence in Medicine
    [Web link]


    Papers That Cite This Data Set1:


    Vassilis Athitsos and Stan Sclaroff. Boosting Nearest Neighbor Classifiers for Multiclass Recognition. Boston University Computer Science Tech. Report No, 2004-006. 2004.  [View Context].

    Gisele L. Pappa and Alex Alves Freitas and Celso A A Kaestner. Attribute Selection with a Multi-objective Genetic Algorithm. SBIA. 2002.  [View Context].

    Rafael S. Parpinelli and Heitor S. Lopes and Alex Alves Freitas. PART FOUR: ANT colonY OPTIMIZATION AND IMMUNE SYSTEMS Chapter X An Ant colony Algor


    Original Owners:

    1. Nilsel Ilter, M.D., Ph.D.,
    Gazi University,
    School of Medicine
    06510 Ankara, Turkey
    Phone: +90 (312) 214 1080

    2. H. Altay Guvenir, PhD.,
    Bilkent University,
    Department of Computer Engineering and Information Science,
    06533 Ankara, Turkey
    Phone: +90 (312) 266 4133
    Email: guvenir '@' cs.bilkent.edu.tr

    Donor:

    H. Altay Guvenir,
    Bilkent University,
    Department of Computer Engineering and Information Science,
    06533 Ankara, Turkey
    Phone: +90 (312) 266 4133
    Email: guvenir '@' cs.bilkent.edu.tr




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