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丙型肝炎、纤维化、肝硬化数据集

丙型肝炎、纤维化、肝硬化数据集

Scene:

Medical,Life

Data Type:

Classification
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Data Preview ? 45.1K

    Data Structure ?

    *数据结构实际以真实数据为准

    Creators: Ralf Lichtinghagen, Frank Klawonn, Georg Hoffmann
    Donor: Ralf Lichtinghagen: Institute of Clinical Chemistry; Medical University Hannover (MHH); Hannover, Germany; lichtinghagen.ralf '@' mh-hannover.de
    Donor: Frank Klawonn; Helmholtz Centre for Infection Research; Braunschweig, Germany; frank.klawonn '@' helmholtz-hzi.de
    Donor: Georg Hoffmann; Trillium GmbH; Grafrath, Germany; georg.hoffmann '@' trillium.de


    Data Set Information:

    The target attribute for classification is Category (blood donors vs. Hepatitis C (including its progress ('just' Hepatitis C, Fibrosis, Cirrhosis).


    Attribute Information:

    All attributes except Category and Sex are numerical. The laboratory data are the attributes 5-14.
    1) X (Patient ID/No.)
    2) Category (diagnosis) (values: '0=Blood Donor', '0s=suspect Blood Donor', '1=Hepatitis', '2=Fibrosis', '3=Cirrhosis')
    3) Age (in years)
    4) Sex (f,m)
    5) ALB
    6) ALP
    7) ALT
    8) AST
    9) BIL
    10) CHE
    11) CHOL
    12) CREA
    13) GGT
    14) PROT


    Relevant Papers:

    Lichtinghagen R et al. J Hepatol 2013; 59: 236-42
    Hoffmann G et al. Using machine learning techniques to generate laboratory diagnostic pathways a€“ a case study. J Lab Precis Med 2018; 3: 58-67



    Citation Request:

    Please refer to the Machine Learning Repository's citation policy

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