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The synergism of spatial metabolomics and morphometry improves machine learning‐based renal tumour subtype classification
| Autores principales: | , , , , , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
John Wiley and Sons Inc.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8858620/ https://www.ncbi.nlm.nih.gov/pubmed/35184396 http://dx.doi.org/10.1002/ctm2.666 |
| _version_ | 1784654278779994112 |
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| author | Prade, Verena M. Sun, Na Shen, Jian Feuchtinger, Annette Kunzke, Thomas Buck, Achim Schraml, Peter Moch, Holger Schwamborn, Kristina Autenrieth, Michael Gschwend, Jürgen E. Erlmeier, Franziska Hartmann, Arndt Walch, Axel |
| author_facet | Prade, Verena M. Sun, Na Shen, Jian Feuchtinger, Annette Kunzke, Thomas Buck, Achim Schraml, Peter Moch, Holger Schwamborn, Kristina Autenrieth, Michael Gschwend, Jürgen E. Erlmeier, Franziska Hartmann, Arndt Walch, Axel |
| author_sort | Prade, Verena M. |
| collection | PubMed |
| description | |
| format | Online Article Text |
| id | pubmed-8858620 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2022 |
| publisher | John Wiley and Sons Inc. |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-88586202022-03-31 The synergism of spatial metabolomics and morphometry improves machine learning‐based renal tumour subtype classification Prade, Verena M. Sun, Na Shen, Jian Feuchtinger, Annette Kunzke, Thomas Buck, Achim Schraml, Peter Moch, Holger Schwamborn, Kristina Autenrieth, Michael Gschwend, Jürgen E. Erlmeier, Franziska Hartmann, Arndt Walch, Axel Clin Transl Med Letter to Editor John Wiley and Sons Inc. 2022-02-20 /pmc/articles/PMC8858620/ /pubmed/35184396 http://dx.doi.org/10.1002/ctm2.666 Text en © 2022 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
| spellingShingle | Letter to Editor Prade, Verena M. Sun, Na Shen, Jian Feuchtinger, Annette Kunzke, Thomas Buck, Achim Schraml, Peter Moch, Holger Schwamborn, Kristina Autenrieth, Michael Gschwend, Jürgen E. Erlmeier, Franziska Hartmann, Arndt Walch, Axel The synergism of spatial metabolomics and morphometry improves machine learning‐based renal tumour subtype classification |
| title | The synergism of spatial metabolomics and morphometry improves machine learning‐based renal tumour subtype classification |
| title_full | The synergism of spatial metabolomics and morphometry improves machine learning‐based renal tumour subtype classification |
| title_fullStr | The synergism of spatial metabolomics and morphometry improves machine learning‐based renal tumour subtype classification |
| title_full_unstemmed | The synergism of spatial metabolomics and morphometry improves machine learning‐based renal tumour subtype classification |
| title_short | The synergism of spatial metabolomics and morphometry improves machine learning‐based renal tumour subtype classification |
| title_sort | synergism of spatial metabolomics and morphometry improves machine learning‐based renal tumour subtype classification |
| topic | Letter to Editor |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8858620/ https://www.ncbi.nlm.nih.gov/pubmed/35184396 http://dx.doi.org/10.1002/ctm2.666 |
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