يعرض 1 - 4 نتائج من 4 نتيجة بحث عن '"Wan Fung Chui"', وقت الاستعلام: 0.86s تنقيح النتائج
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    دورية أكاديمية
    Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes

    المؤلفون: James A. Diao, Jason K. Wang, Wan Fung Chui, Victoria Mountain, Sai Chowdary Gullapally, Ramprakash Srinivasan, Richard N. Mitchell, Benjamin Glass, Sara Hoffman, Sudha K. Rao, Chirag Maheshwari, Abhik Lahiri, Aaditya Prakash, Ryan McLoughlin, Jennifer K. Kerner, Murray B. Resnick, Michael C. Montalto, Aditya Khosla, Ilan N. Wapinski, Andrew H. Beck, Hunter L. Elliott, Amaro Taylor-Weiner

    المصدر: Nature Communications, Vol 12, Iss 1, Pp 1-15 (2021)

    مصطلحات موضوعية: Science

    وصف الملف: electronic resource

    Relation: https://doaj.org/toc/2041-1723

    URL الوصول: https://doaj.org/article/05d507904fe140cd941a3a33245b3716

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  2. 2
    Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes

    المؤلفون: Victoria Mountain, Ramprakash Srinivasan, Michael Christopher Montalto, Abhik Lahiri, Sara Hoffman, Amaro Taylor-Weiner, Murray B. Resnick, Benjamin Glass, Jason K Wang, Hunter L. Elliott, Andrew H. Beck, Sai Chowdary Gullapally, Ilan Wapinski, Aaditya Prakash, Chirag Maheshwari, Aditya Khosla, James A. Diao, Jennifer K. Kerner, Ryan McLoughlin, Sudha K. Rao, Richard N. Mitchell, Wan Fung Chui

    المصدر: Nature Communications
    Nature Communications, Vol 12, Iss 1, Pp 1-15 (2021)

    مصطلحات موضوعية: 0301 basic medicine, Pathology, medicine.medical_specialty, Computer science, Science, General Physics and Astronomy, Predictive markers, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, Deep Learning, 0302 clinical medicine, Neoplasms, Machine learning, Image Processing, Computer-Assisted, Tumor Microenvironment, medicine, Humans, Pathology, Molecular, Precision Medicine, Interpretability, Multidisciplinary, business.industry, Deep learning, Cancer, General Chemistry, medicine.disease, Phenotype, 030104 developmental biology, 030220 oncology & carcinogenesis, Cancer imaging, Artificial intelligence, business, Homologous Recombination Deficiency, Algorithms

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e074119e16b4713a8ec93a1febded1fe
    https://doi.org/10.1038/s41467-021-21896-9

    Find this article in full text from Springer Verlag. Find this article in full text from ProQuest
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  3. 3
    Dense, high-resolution mapping of cells and tissues from pathology images for the interpretable prediction of molecular phenotypes in cancer

    المؤلفون: Benjamin Glass, Victoria Mountain, Sudha K. Rao, Andrew H. Beck, Aditya Khosla, Jason K Wang, Hunter L. Elliott, Abhik Lahiri, Murray B. Resnick, Ilan Wapinski, Chirag Maheshwari, Wan Fung Chui, Michael Christopher Montalto, Richard N. Mitchell, James A. Diao, Jennifer K. Kerner, Amaro Taylor-Weiner

    مصطلحات موضوعية: medicine.medical_specialty, Tumor microenvironment, Pathology, Computer science, medicine, Cancer, High resolution, Histopathology, Multiple tumors, medicine.disease, Phenotype, Protein expression, Immune checkpoint

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::2565e74a5cbb8d40aad50a8065713a3f
    https://doi.org/10.1101/2020.08.02.233197

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  4. 4
    Abstract PD6-04: Deep-learning based prediction of homologous recombination deficiency (hrd) status from histological features in breast cancer; a research study

    المؤلفون: Andrew H. Beck, Aryan Pedawi, Michael Christopher Montalto, Benjamin Glass, James A. Diao, Aditya Khosla, Wan Fung Chui, Amaro Taylor-Weiner, Ilan Wapinski, Hunter L. Elliott, Jason K. Wang, Victoria Mountain

    المصدر: Cancer Research. 81:PD6-04

    مصطلحات موضوعية: Cancer Research, Breast cancer, Oncology, Cancer research, medicine, Biology, medicine.disease, Homologous Recombination Deficiency

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::12cfa62e34921323439e3eee7fc23571
    https://doi.org/10.1158/1538-7445.sabcs20-pd6-04

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