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State‐of‐the‐art machine learning improves predictive accuracy of 1‐year survival after heart transplantation
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
John Wiley and Sons Inc.
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8318480/ https://www.ncbi.nlm.nih.gov/pubmed/34008301 http://dx.doi.org/10.1002/ehf2.13425 |
| _version_ | 1783730254131494912 |
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| author | Kampaktsis, Polydoros N. Moustakidis, Serafeim Tzani, Aspasia Doulamis, Ilias P. Drosou, Anastasios Tzoumas, Andreas Asleh, Rabea Briasoulis, Alexandros |
| author_facet | Kampaktsis, Polydoros N. Moustakidis, Serafeim Tzani, Aspasia Doulamis, Ilias P. Drosou, Anastasios Tzoumas, Andreas Asleh, Rabea Briasoulis, Alexandros |
| author_sort | Kampaktsis, Polydoros N. |
| collection | PubMed |
| description | |
| format | Online Article Text |
| id | pubmed-8318480 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2021 |
| publisher | John Wiley and Sons Inc. |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-83184802021-07-31 State‐of‐the‐art machine learning improves predictive accuracy of 1‐year survival after heart transplantation Kampaktsis, Polydoros N. Moustakidis, Serafeim Tzani, Aspasia Doulamis, Ilias P. Drosou, Anastasios Tzoumas, Andreas Asleh, Rabea Briasoulis, Alexandros ESC Heart Fail Letters to the Editor John Wiley and Sons Inc. 2021-05-18 /pmc/articles/PMC8318480/ /pubmed/34008301 http://dx.doi.org/10.1002/ehf2.13425 Text en © 2021 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
| spellingShingle | Letters to the Editor Kampaktsis, Polydoros N. Moustakidis, Serafeim Tzani, Aspasia Doulamis, Ilias P. Drosou, Anastasios Tzoumas, Andreas Asleh, Rabea Briasoulis, Alexandros State‐of‐the‐art machine learning improves predictive accuracy of 1‐year survival after heart transplantation |
| title | State‐of‐the‐art machine learning improves predictive accuracy of 1‐year survival after heart transplantation |
| title_full | State‐of‐the‐art machine learning improves predictive accuracy of 1‐year survival after heart transplantation |
| title_fullStr | State‐of‐the‐art machine learning improves predictive accuracy of 1‐year survival after heart transplantation |
| title_full_unstemmed | State‐of‐the‐art machine learning improves predictive accuracy of 1‐year survival after heart transplantation |
| title_short | State‐of‐the‐art machine learning improves predictive accuracy of 1‐year survival after heart transplantation |
| title_sort | state‐of‐the‐art machine learning improves predictive accuracy of 1‐year survival after heart transplantation |
| topic | Letters to the Editor |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8318480/ https://www.ncbi.nlm.nih.gov/pubmed/34008301 http://dx.doi.org/10.1002/ehf2.13425 |
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