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Artificial Intelligence in Health                                         Cirrhosis prediction in hepatitis C



               2014;15(1):1929-1958.                           21.  Paszke A, Gross S, Chintala S, et al. Automatic Differentiation
                                                                  in Pytorch. Available from: https://openreview.net/
               doi: 10.5555/2627435.2670313
                                                                  pdf?id=BJJsrmfCZ [Last accessed on 2023 Feb 18].
            17.  Tang W, Ma J, Waljee AK, Zhu J. Semi-supervised joint
               learning for longitudinal clinical events classification using   22.  Graf E, Schmoor C, Sauerbrei W, Schumacher M. Assessment
               neural network models. Stat. 2020;9:e305.          and comparison of prognostic classification schemes for
                                                                  survival data. Stat Med. 1999;18(17-18):2529-2545.
               doi: 10.1002/sta4.305
                                                                  doi: 10.1002/(SICI)1097-0258(19990915/30)18:17/18<2529::
            18.  Stekhoven D, Bühlmann P. MissForest  -  non-parametric   AID-SIM274>3.0.CO;2-5
               missing  value  imputation  for  mixed-type  data.
               Bioinformatics. 2012;28(1):112-118.             23.  Li J, Chen X, Hovy E, Jurafsky D. Visualizing and
                                                                  understanding neural models in NLP. arXiv. Preprint posted
               doi: 10.1093/bioinformatics/btr597                 online 2016.
            19.  Boyd K, Eng KH, Page CD. Area under the precision-recall      doi: 10.48550/arXiv.1506.01066
               curve: Point estimates and confidence intervals. In:
               Blockeel  H, Kersting K, Nijssen S, Železný F, editors.   24.  Becker U, Deis A, Sørensen TI, et al. Prediction of risk of
               Machine Learning and Knowledge Discovery in Databases.   liver disease by alcohol intake, sex, and age: A prospective
               Springer; 2013. p. 451-466.                        population study. Hepatology. 1996;23(5):1025-1029.
               doi: 10.1007/978-3-642-40994-3_29                  doi: 10.1002/hep.510230513
            20.  Pedregosa F, Varoquaux G, Gramfort A,  et al. Scikit-  25.  Liberal R, Grant C, Mieli-Vergani G, Vergani D. Autoimmune
               learn: Machine learning in Python.  J  Mach Learn Res.   hepatitis: A  comprehensive review.  J  Autoimmun.
               2011;12:2825-2830.                                 2013;41:126-139.
               doi: 10.5555/1953048.2078195                       doi: 10.1016/j.jaut.2012.11.002
















































            Volume 2 Issue 2 (2025)                         99                               doi: 10.36922/aih.4671
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