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The need for validation of MI GPSai in patients with CUP: Comment on: “Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type” by J Abraham et al.
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Neoplasia Press
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236542/ https://www.ncbi.nlm.nih.gov/pubmed/34167744 http://dx.doi.org/10.1016/j.tranon.2021.101092 |
| _version_ | 1783714559659343872 |
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| author | Greco, F. Anthony |
| author_facet | Greco, F. Anthony |
| author_sort | Greco, F. Anthony |
| collection | PubMed |
| description | |
| format | Online Article Text |
| id | pubmed-8236542 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2021 |
| publisher | Neoplasia Press |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-82365422021-07-12 The need for validation of MI GPSai in patients with CUP: Comment on: “Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type” by J Abraham et al. Greco, F. Anthony Transl Oncol Letter to the Editor Neoplasia Press 2021-06-21 /pmc/articles/PMC8236542/ /pubmed/34167744 http://dx.doi.org/10.1016/j.tranon.2021.101092 Text en © 2021 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
| spellingShingle | Letter to the Editor Greco, F. Anthony The need for validation of MI GPSai in patients with CUP: Comment on: “Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type” by J Abraham et al. |
| title | The need for validation of MI GPSai in patients with CUP: Comment on: “Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type” by J Abraham et al. |
| title_full | The need for validation of MI GPSai in patients with CUP: Comment on: “Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type” by J Abraham et al. |
| title_fullStr | The need for validation of MI GPSai in patients with CUP: Comment on: “Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type” by J Abraham et al. |
| title_full_unstemmed | The need for validation of MI GPSai in patients with CUP: Comment on: “Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type” by J Abraham et al. |
| title_short | The need for validation of MI GPSai in patients with CUP: Comment on: “Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type” by J Abraham et al. |
| title_sort | need for validation of mi gpsai in patients with cup: comment on: “machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type” by j abraham et al. |
| topic | Letter to the Editor |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236542/ https://www.ncbi.nlm.nih.gov/pubmed/34167744 http://dx.doi.org/10.1016/j.tranon.2021.101092 |
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