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

scientific article published on 23 May 2016

Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis is …
instance of (P31):
scholarly articleQ13442814

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P6179Dimensions Publication ID1041372741
P356DOI10.1038/SREP26286
P2888exact matchhttps://scigraph.springernature.com/pub.10.1038/srep26286
P932PMC publication ID4876324
P698PubMed publication ID27212078

P50authorPeter BultQ57159574
Bram van GinnekenQ58101398
Meyke HermsenQ61161842
Geert LitjensQ48542387
P2093author name stringClara I Sánchez
Iris Nagtegaal
Christina Hulsbergen-van de Kaa
Iringo Kovacs
Jeroen van der Laak
Nadya Timofeeva
P2860cites workDeep learningQ28018765
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 systemsQ28269254
Micrometastases or isolated tumor cells and the outcome of breast cancer.Q53377954
Hematoxylin and Eosin Staining of Tissue and Cell SectionsQ58006521
Mitosis Detection in Breast Cancer Histology Images with Deep Neural NetworksQ62065704
A deep learning architecture for image representation, visual interpretability and automated basal-cell carcinoma cancer detectionQ62497981
To biopsy or not to biopsy--thou shall think twiceQ83426608
Robust Cell Detection and Segmentation in Histopathological Images Using Sparse Reconstruction and Stacked Denoising AutoencodersQ88654046
Histopathological image analysis: a reviewQ28750188
Breast cancer prognosis and occult lymph node metastases, isolated tumor cells, and micrometastasesQ33535173
Effect of occult metastases on survival in node-negative breast cancerQ34159750
Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network featuresQ35686841
The 2005 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic CarcinomaQ36227180
Lymphatic mapping and sentinel lymph node biopsy in early-stage breast carcinoma: a metaanalysisQ36331580
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 NodQ37422610
A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images.Q37616337
Pathology evaluation of sentinel lymph nodes in breast cancer: protocol recommendations and rationaleQ37740945
Automated Grading of Gliomas using Deep Learning in Digital Pathology Images: A modular approach with ensemble of convolutional neural networksQ38614807
P275copyright licenseCreative Commons Attribution 4.0 InternationalQ20007257
P6216copyright statuscopyrightedQ50423863
P407language of work or nameEnglishQ1860
P921main subjectdeep learningQ197536
P304page(s)26286
P577publication date2016-05-23
P1433published inScientific ReportsQ2261792
P1476titleDeep learning as a tool for increased accuracy and efficiency of histopathological diagnosis
P478volume6

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