Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis. - Wikidata - wikimedia - TriplyDB

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

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

http://www.wikidata.org/entity/Q36925087

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Automating cell detection and classification in human brain fluorescent microscopy images using dictionary learning and sparse coding.Classification of breast cancer histology images using Convolutional Neural Networks.Breast Cancer Multi-classification from Histopathological Images with Structured Deep Learning Model.Antibody-supervised deep learning for quantification of tumor-infiltrating immune cells in hematoxylin and eosin stained breast cancer samples.A preliminary examination of the diagnostic value of deep learning in hip osteoarthritis.Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer.Self-Recalibrating Surface EMG Pattern Recognition for Neuroprosthesis Control Based on Convolutional Neural Network.Using deep belief network modelling to characterize differences in brain morphometry in schizophrenia.Automated Classification of Lung Cancer Types from Cytological Images Using Deep Convolutional Neural Networks.Accuracy of deep learning, a machine-learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment.Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning.Grading of invasive breast carcinoma through Grassmannian VLAD encoding.Machine learning to detect signatures of disease in liquid biopsies - a user's guide.Interactive phenotyping of large-scale histology imaging data with HistomicsML.A Deep-Learning System for Fully-Automated Peripherally Inserted Central Catheter (PICC) Tip Detection.Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.Leveraging uncertainty information from deep neural networks for disease detection.Long-term prognosis of young breast cancer patients (≤40 years) who did not receive adjuvant systemic treatment: protocol for the PARADIGM initiative cohort study.Pathology, proteomics and the pathway to personalised medicine.Automated Interpretation of Blood Culture Gram Stains using a Deep Convolutional Neural Network.Automatic labeling of molecular biomarkers of immunohistochemistry images using fully convolutional networks.Histopathology: ditch the slides, because digital and 3D are on show.Multiscale High-Level Feature Fusion for Histopathological Image Classification.Deep learning based tissue analysis predicts outcome in colorectal cancer.Opportunities and obstacles for deep learning in biology and medicine.An improved deep learning approach for detection of thyroid papillary cancer in ultrasound images.BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data.A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue.Visualizing histopathologic deep learning classification and anomaly detection using nonlinear feature space dimensionality reduction.Deep Learning Solutions for Classifying Patients on Opioid Use.Predicting cancer outcomes from histology and genomics using convolutional networks.Precision histology: how deep learning is poised to revitalize histomorphology for personalized cancer care.1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset.A Multi-scale U-Net for Semantic Segmentation of Histological Images from Radical Prostatectomies.Machine Learning Methods for Histopathological Image Analysis Accuracy of deep learning, a machine learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting idiopathic macular holes High-throughput ovarian follicle counting by an innovative deep learning approach A Transfer Learning Approach for Microstructure Reconstruction and Structure-property Predictions Automated Gleason grading of prostate cancer tissue microarrays via deep learning

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

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Deep learning as a tool for in ...... f histopathological diagnosis.

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Bram van Ginneken

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Christina Hulsbergen-van de Kaa

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Clara I Sánchez

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Iringo Kovacs

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Iris Nagtegaal

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Jeroen van der Laak

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Comparison of the prognostic value of Scarff-Bloom-Richardson and Nottingham histological grades in a series of 825 cases of breast cancer: major importance of the mitotic count as a component of both grading systems

Histopathological image analysis: a review

Breast cancer prognosis and occult lymph node metastases, isolated tumor cells, and micrometastases.

Effect of occult metastases on survival in node-negative breast cancer.

Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features.

The 2005 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma.

Lymphatic mapping and sentinel lymph node biopsy in early-stage breast carcinoma: a metaanalysis.

Prognostic implications of isolated tumor cells and micrometastases in sentinel nodes of patients with invasive breast cancer: 10-year analysis of patients enrolled in the prospective East Carolina University/Anne Arundel Medical Center Sentinel Nod

Pathology evaluation of sentinel lymph nodes in breast cancer: protocol recommendations and rationale.

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10.1038/SREP26286

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