Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis

Litjens, Geert, Sánchez, Clara I., Timofeeva, Nadya, Hermsen, Meyke, Nagtegaal, Iris, Kovacs, Iringo, Hulsbergen - van de Kaa, Christina, Bult, Peter +2 more·2016·Scientific Reports

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  14. Classification of histopathological whole slide images based on multiple weighted semi-supervised domain adaptation
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  16. Weakly Supervised Segmentation with Point Annotations for Histopathology Images via Contrast-Based Variational Model
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  50. No pixel-level annotations needed
    Jeroen A. W. M. van der Laak, Francesco Ciompi, Geert J. S. Litjens · 2019 · Nature Biomedical Engineering
  51. Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images
    David Dov, Shahar Z. Kovalsky, Cohen, Jonathan, Danielle Elliott Range, Ricardo Henao, Lawrence Carin · 2019 · arXiv (Cornell University)
  52. From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine
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    Anna Gummeson, Ida Arvidsson, Mattias Ohlsson, Niels Chr. Overgaard, Agnieszka Krzyzanowska, Anders Heyden, Anders S Bjartell, Kalle Åström · 2017 · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
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  60. A dynamic uncertainty-aware ensemble model: Application to lung cancer segmentation in digital pathology
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  65. DeepHealth: Review and challenges of artificial intelligence in health informatics
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  66. Automatic annotation of cervical vertebrae in videofluoroscopy images via deep learning
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  74. Deep learning for high-resolution and high-sensitivity interferometric phase contrast imaging
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