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心力衰竭临床记录数据集

心力衰竭临床记录数据集

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Life Classification

Provide the names, email addresses, institutions, and other contact information of the donors and creators of the data s......

数据结构 ? 12K

    Data Structure ?

    * 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

    Provide the names, email addresses, institutions, and other contact information of the donors and creators of the data set.The original dataset version was collected by Tanvir Ahmad, Assia Munir, Sajjad Haider Bhatti, Muhammad Aftab, and Muhammad Ali Raza (Government College University, Faisalabad, Pakistan) and made available by them on FigShare under the Attribution 4.0 International (CC BY 4.0: freedom to share and adapt the material) copyright in July 2017.

    The current version of the dataset was elaborated by Davide Chicco (Krembil Research Institute, Toronto, Canada) and donated to the University of California Irvine Machine Learning Repository under the same Attribution 4.0 International (CC BY 4.0) copyright in January 2020. Davide Chicco can be reached at <davidechicco '@' davidechicco.it>


    Data Set Information:

    A detailed description of the dataset can be found in the Dataset section of the following paper:

    Davide Chicco, Giuseppe Jurman: "Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone". BMC Medical Informatics and Decision Making 20, 16 (2020). [Web link]


    Attribute Information:

    Thirteen (13) clinical features:

    - age: age of the patient (years)
    - anaemia: decrease of red blood cells or hemoglobin (boolean)
    - high blood pressure: if the patient has hypertension (boolean)
    - creatinine phosphokinase  (CPK): level of the CPK enzyme in the blood (mcg/L)
    - diabetes: if the patient has diabetes (boolean)
    - ejection fraction: percentage of blood leaving the heart at each contraction  (percentage)
    - platelets: platelets in the blood (kiloplatelets/mL)
    - sex: woman or man (binary)
    - serum creatinine: level of serum creatinine in the blood (mg/dL)
    - serum sodium: level of serum sodium in the blood (mEq/L)
    - smoking: if the patient smokes or not (boolean)
    - time: follow-up period (days)
    - [target] death event: if the patient deceased during the follow-up period (boolean)

    For more information, please check Table 1, Table 2, and Table 3 of the following paper:

    Davide Chicco, Giuseppe Jurman: "Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone". BMC Medical Informatics and Decision Making 20, 16 (2020). [Web link]


    Relevant Papers:

    Original dataset version:

    Tanvir Ahmad, Assia Munir, Sajjad Haider Bhatti, Muhammad Aftab, and Muhammad Ali Raza: "Survival analysis of heart failure patients: a case study". PLoS ONE 12(7), 0181001 (2017). [Web link]  

    Current dataset version on the UCI ML Repository:

    Davide Chicco, Giuseppe Jurman: "Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone". BMC Medical Informatics and Decision Making 20, 16 (2020). [Web link]


    Citation Request:

    Davide Chicco, Giuseppe Jurman: "Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone". BMC Medical Informatics and Decision Making 20, 16 (2020). [Web link]

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