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Title:           Assessment of portal hypertension severity using machine learning models in patients with compensated cirrhosis
Subject:         Journal of Hepatology, 78 (2023) 390-400. doi:10.1016/j.jhep.2022.09.012
Author:          Jiří Reiniš
Creator:         Elsevier
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     Item: 
      Title: Assessment of portal hypertension severity using machine learning models in patients with compensated cirrhosis
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       Item: 
        Title: Introduction
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       Item: 
        Title: Patients and methods
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         Item: 
          Title: Study design, participant selection, and recorded parameters
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         Item: 
          Title: Data pre-processing and exploration
          Destination: slink2
         Item: 
          Title: Development of MLMs
          Destination: slink3
         Item: 
          Title: Feature selection for MLMs: recursive feature elimination
          Destination: slink4
         Item: 
          Title: Robust estimation of classification performance using 5-fold cross-validation
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         Item: 
          Title: External model validation
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         Item: 
          Title: Extraction of LR coefficients
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         Item: 
          Title: Prediction of HVPG value with regression
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       Item: 
        Title: Results
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         Item: 
          Title: Patient characteristics
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         Item: 
          Title: Selection of widely available parameters for assessment of PH severity
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         Item: 
          Title: Performance of the Vienna-trained MLMs in external validation
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         Item: 
          Title: Evaluation of the overall performance of the MLMs in the merged cACLD cohort
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         Item: 
          Title: Contribution of disease activity and aetiology to model performance
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         Item: 
          Title: Balancing datasets does not significantly improve the predictive power
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         Item: 
          Title: The formula for prediction of severe PH with LR
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        Title: Discussion
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        Title: Abbreviations
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        Title: Financial support
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        Title: Conflict of interest
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        Title: Data availability statement
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        Title: Supplementary data
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        Title: References
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    Title: Assessment of portal hypertension severity using machine learning models in patients with compensated cirrhosis
    Author: Jiří Reiniš
    Subject: Journal of Hepatology, 78 (2023) 390-400. doi:10.1016/j.jhep.2022.09.012
    Creator: Elsevier
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  Checksum: 92052b57
   Type: CRC32
  Checksum: d432b149357c24c566378bd8f7a7a620
   Type: MD5
  Checksum: defd018790a7ee840d9047f11f3e65440d487ea6
   Type: SHA-1
  Checksum: b2a68fdfc9a5b0b62916622f0d01a0137308700a3cb42b8a515dd6cf68f42565
   Type: SHA-256