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Is machine learning-based assessment of tumor-infiltrating lymphocytes on standard histologic images associated with outcomes of immunotherapy in patients with NSCLC?
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
AME Publishing Company
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10267919/ https://www.ncbi.nlm.nih.gov/pubmed/37324072 http://dx.doi.org/10.21037/jtd-22-1862 |
| _version_ | 1785059027170885632 |
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| author | Inamura, Kentaro Shigematsu, Yasuyuki |
| author_facet | Inamura, Kentaro Shigematsu, Yasuyuki |
| author_sort | Inamura, Kentaro |
| collection | PubMed |
| description | |
| format | Online Article Text |
| id | pubmed-10267919 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2023 |
| publisher | AME Publishing Company |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-102679192023-06-15 Is machine learning-based assessment of tumor-infiltrating lymphocytes on standard histologic images associated with outcomes of immunotherapy in patients with NSCLC? Inamura, Kentaro Shigematsu, Yasuyuki J Thorac Dis Letter to the Editor AME Publishing Company 2023-04-23 2023-05-30 /pmc/articles/PMC10267919/ /pubmed/37324072 http://dx.doi.org/10.21037/jtd-22-1862 Text en 2023 Journal of Thoracic Disease. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
| spellingShingle | Letter to the Editor Inamura, Kentaro Shigematsu, Yasuyuki Is machine learning-based assessment of tumor-infiltrating lymphocytes on standard histologic images associated with outcomes of immunotherapy in patients with NSCLC? |
| title | Is machine learning-based assessment of tumor-infiltrating lymphocytes on standard histologic images associated with outcomes of immunotherapy in patients with NSCLC? |
| title_full | Is machine learning-based assessment of tumor-infiltrating lymphocytes on standard histologic images associated with outcomes of immunotherapy in patients with NSCLC? |
| title_fullStr | Is machine learning-based assessment of tumor-infiltrating lymphocytes on standard histologic images associated with outcomes of immunotherapy in patients with NSCLC? |
| title_full_unstemmed | Is machine learning-based assessment of tumor-infiltrating lymphocytes on standard histologic images associated with outcomes of immunotherapy in patients with NSCLC? |
| title_short | Is machine learning-based assessment of tumor-infiltrating lymphocytes on standard histologic images associated with outcomes of immunotherapy in patients with NSCLC? |
| title_sort | is machine learning-based assessment of tumor-infiltrating lymphocytes on standard histologic images associated with outcomes of immunotherapy in patients with nsclc? |
| topic | Letter to the Editor |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10267919/ https://www.ncbi.nlm.nih.gov/pubmed/37324072 http://dx.doi.org/10.21037/jtd-22-1862 |
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