Deep learning for endometrial cancer subtyping and predicting tumor mutational burden from histopathological slides.
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| Title: | Deep learning for endometrial cancer subtyping and predicting tumor mutational burden from histopathological slides. |
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| Authors: | Wang CW; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. cweiwang@mail.ntust.edu.tw., Firdi NP; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan., Lee YC; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan., Chu TC; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan., Muzakky H; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan., Liu TC; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan., Lai PJ; Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan., Chao TK; Institute of Pathology and Parasitology, National Defense Medical Center, Taipei, Taiwan. chaotai.kuang@msa.hinet.net.; Department of Pathology, Tri-Service General Hospital, Taipei, Taiwan. chaotai.kuang@msa.hinet.net. |
| Source: | NPJ precision oncology [NPJ Precis Oncol] 2024 Dec 21; Vol. 8 (1), pp. 287. Date of Electronic Publication: 2024 Dec 21. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Nature Country of Publication: England NLM ID: 101708166 Publication Model: Electronic Cited Medium: Print ISSN: 2397-768X (Print) Linking ISSN: 2397768X NLM ISO Abbreviation: NPJ Precis Oncol Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2397-768X |
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| DOI: | 10.1038/s41698-024-00766-9 |
