Rezultaty 1 - 10 Rezultaty od 10 Dla wyszukiwania 'Lee A D Cooper', Czas wyszukiwania: 0,03s Redukuj rezultaty
  1. 1
    Deep Gaussian Processes for Classification With Multiple Noisy Annotators. Application to Breast Cancer Tissue Classification

    Deep Gaussian Processes for Classification With Multiple Noisy Annotators. Application to Breast Cancer Tissue Classification od Miguel Lopez-Perez, Pablo Morales-Alvarez, Lee A. D. Cooper, Rafael Molina, Aggelos K. Katsaggelos

    Wydane 2023-01-01
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  2. 2
    A panoptic segmentation dataset and deep-learning approach for explainable scoring of tumor-infiltrating lymphocytes

    A panoptic segmentation dataset and deep-learning approach for explainable scoring of tumor-infiltrating lymphocytes od Shangke Liu, Mohamed Amgad, Deeptej More, Muhammad A. Rathore, Roberto Salgado, Lee A. D. Cooper

    Wydane 2024-06-01
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  3. 3
    High expression of MKK3 is associated with worse clinical outcomes in African American breast cancer patients

    High expression of MKK3 is associated with worse clinical outcomes in African American breast cancer patients od Xuan Yang, Mohamed Amgad, Lee A. D. Cooper, Yuhong Du, Haian Fu, Andrey A. Ivanov

    Wydane 2020-09-01
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  4. 4
    Learning from crowds in digital pathology using scalable variational Gaussian processes

    Learning from crowds in digital pathology using scalable variational Gaussian processes od Miguel López-Pérez, Mohamed Amgad, Pablo Morales-Álvarez, Pablo Ruiz, Lee A. D. Cooper, Rafael Molina, Aggelos K. Katsaggelos

    Wydane 2021-06-01
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  5. 5
    Translating prognostic quantification of c-MYC and BCL2 from tissue microarrays to whole slide images in diffuse large B-cell lymphoma using deep learning

    Translating prognostic quantification of c-MYC and BCL2 from tissue microarrays to whole slide images in diffuse large B-cell lymphoma using deep learning od Thomas E. Tavolara, M. Khalid Khan Niazi, Andrew L. Feldman, David L. Jaye, Christopher Flowers, Lee A.D. Cooper, Metin N. Gurcan

    Wydane 2024-01-01
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  6. 6
    The proneural molecular signature is enriched in oligodendrogliomas and predicts improved survival among diffuse gliomas.

    The proneural molecular signature is enriched in oligodendrogliomas and predicts improved survival among diffuse gliomas. od Lee A D Cooper, David A Gutman, Qi Long, Brent A Johnson, Sharath R Cholleti, Tahsin Kurc, Joel H Saltz, Daniel J Brat, Carlos S Moreno

    Wydane 2010-09-01
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  7. 7
    A high-performance spatial database based approach for pathology imaging algorithm evaluation

    A high-performance spatial database based approach for pathology imaging algorithm evaluation od Fusheng Wang, Jun Kong, Jingjing Gao, Lee A.D. Cooper, Tahsin Kurc, Zhengwen Zhou, David Adler, Cristobal Vergara-Niedermayr, Bryan Katigbak, Daniel J Brat, Joel H Saltz

    Wydane 2013-01-01
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  8. 8
    MEDICI: Mining Essentiality Data to Identify Critical Interactions for Cancer Drug Target Discovery and Development.

    MEDICI: Mining Essentiality Data to Identify Critical Interactions for Cancer Drug Target Discovery and Development. od Sahar Harati, Lee A D Cooper, Josue D Moran, Felipe O Giuste, Yuhong Du, Andrei A Ivanov, Margaret A Johns, Fadlo R Khuri, Haian Fu, Carlos S Moreno

    Wydane 2017-01-01
    Dokumenty pełnotekstowe
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  9. 9
    Correction: Corrigendum: The OncoPPi network of cancer-focused protein–protein interactions to inform biological insights and therapeutic strategies

    Correction: Corrigendum: The OncoPPi network of cancer-focused protein–protein interactions to inform biological insights and therapeutic strategies od Zenggang Li, Andrei A. Ivanov, Rina Su, Valentina Gonzalez-Pecchi, Qi Qi, Songlin Liu, Philip Webber, Elizabeth McMillan, Lauren Rusnak, Cau Pham, Xiaoqian Chen, Xiulei Mo, Brian Revennaugh, Wei Zhou, Adam Marcus, Sahar Harati, Xiang Chen, Margaret A. Johns, Michael A. White, Carlos S. Moreno, Lee A. D. Cooper, Yuhong Du, Fadlo R. Khuri, Haian Fu

    Wydane 2017-04-01
    Dokumenty pełnotekstowe
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  10. 10
    The OncoPPi network of cancer-focused protein–protein interactions to inform biological insights and therapeutic strategies

    The OncoPPi network of cancer-focused protein–protein interactions to inform biological insights and therapeutic strategies od Zenggang Li, Andrei A. Ivanov, Rina Su, Valentina Gonzalez-Pecchi, Qi Qi, Songlin Liu, Philip Webber, Elizabeth McMillan, Lauren Rusnak, Cau Pham, Xiaoqian Chen, Xiulei Mo, Brian Revennaugh, Wei Zhou, Adam Marcus, Sahar Harati, Xiang Chen, Margaret A. Johns, Michael A. White, Carlos S. Moreno, Lee A. D. Cooper, Yuhong Du, Fadlo R. Khuri, Haian Fu

    Wydane 2017-02-01
    Dokumenty pełnotekstowe
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