Introduction to digital pathology and computer-aided pathology
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Introduction to digital pathology and computer-aided pathology' 의 참고문헌
Why should I trust you? Explaining the predictions of any classifier
Whole slide imaging versus microscopy for primary diagnosis in surgical pathology : a multicenter blinded randomized noninferiority study of 1992 cases(pivotal study)
Validation of digital pathology imaging for primary histopathological diagnosis
Translational AI and deep learning in diagnostic pathology
Too big to ignore : the business case for big data
The practical implementation of artificial intelligence technologies in medicine
Structure-preserving color normalization and sparse stain separation for histological images
StainGAN: stain style transfer for digital histological images
Stain specific standardization of whole-slide histopathological images
Spectral normalization for generative adversarial networks
Similar image search for histopathology : SMILY
Pembrolizumab versus chemotherapy for previously untreated, PD-L1-expressing, locally advanced or metastatic non-small-cell lung cancer(KEYNOTE-042) : a randomised, open-label, controlled, phase 3 trial
Pathology image analysis using segmentation deep learning algorithms
Overview of contemporary guidelines in digital pathology : what is available in 2015 and what still needs to be addressed
Methods for nuclei detection, segmentation, and classification in digital histopathology : a review-current status and future potential
Ki67 labeling index : assessment and prognostic role in gastroenteropancreatic neuroendocrine neoplasms
Introduction to digital image analysis in whole-slide imaging : a white paper from the Digital Pathology Association
Interpretable machine learning
International clinical guidelines for the adoption of digital pathology : a review of technical aspects
Improved automatic detection and segmentation of cell nuclei in histopathology images
Implementation of whole slide imaging for clinical purposes : issues to consider from the perspective of early adopters
Implementation of digital pathology offers clinical and operational increase in efficiency and cost savings
Immunotherapy for lung cancer
Image analysis for neuroblastoma classification : segmentation of cell nuclei
Image analysis and machine learning in digital pathology : Challenges and opportunities
How case based reasoning explained neural networks: an XAI survey of post-hoc explanation-by-example in ANN-CBR twins
Histopathologic variables predict Oncotype DX recurrence score
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
Gastroenteropancreatic neuroendocrine neoplasms : selected pathology review and molecular updates
Future-proofing pathology : the case for clinical adoption of digital pathology
Explaining machine learning classifiers through diverse counterfactual explanations
Evolving artificial neural networks
Digital pathology and artificial intelligence
Digital image analysis outperforms manual biomarker assessment in breast cancer
Deep learning : methods and applications
Crowdsourcing image annotation for nucleus detection and segmentation in computational pathology: evaluating experts, automated methods, and the crowd
Computational pathology definitions, best practices, and recommendations for regulatory guidance : a white paper from the Digital Pathology Association
Comparison of quantification of histochemical staining by hue-saturation-intensity(HSI)transformation and color-deconvolution
Commentary : roles for pathologists in a high-throughput image analysis Team
Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
Case-based reasoning: a textbook
Case-based reasoning : a review
Cancer immunotherapy : harnessing the immune system to battle cancer
Automatic segmentation of cell nuclei in bladder and skin tissue for karyometric analysis
Automatic nuclei segmentation in H&E stained breast cancer histopathology images
Automated measurement of estrogen receptor in breast cancer : a comparison of fluorescent and chromogenic methods of measurement
Attention-based deep multiple instance learning
Artificial intelligence in medicine
Artificial intelligence in lung cancer pathology image analysis
Artificial intelligence in digital pathology : new tools for diagnosis and precision oncology
Artificial intelligence and machine learning in software as a medical device
Artificial intelligence and machine learning in pathology : the present landscape of supervised methods
Artificial intelligence and digital pathology : challenges and opportunities
Artificial Intelligence in Pathology
An automated image analysis methodology for classifying megakaryocytes in chronic myeloproliferative disorders
An alternative reference space for H&E color normalization
American Society of Clinical Oncology/College of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer(unabridged version)
AggNet : deep learning from crowds for mitosis detection in breast cancer histology images
ACTIVIS : visual exploration of industry-scale deep neural network models
A unified architecture for natural language processing: deep neural networks with multitask learning
A unified approach to interpreting model predictions
A nonlinear mapping approach to stain normalization in digital histopathology images using image-specific color deconvolution
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Introduction to digital pathology and computer-aided pathology'
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