标题
Weakly-supervised learning for lung carcinoma classification using deep learning
作者
关键词
-
出版物
Scientific Reports
Volume 10, Issue 1, Pages -
出版商
Springer Science and Business Media LLC
发表日期
2020-06-09
DOI
10.1038/s41598-020-66333-x
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Deep Learning Models for Histopathological Classification of Gastric and Colonic Epithelial Tumours
- (2020) Osamu Iizuka et al. Scientific Reports
- Occurrence of the potent mutagens 2- nitrobenzanthrone and 3-nitrobenzanthrone in fine airborne particles
- (2019) Aldenor G. Santos et al. Scientific Reports
- Convolutional neural networks can accurately distinguish four histologic growth patterns of lung adenocarcinoma in digital slides
- (2019) Arkadiusz Gertych et al. Scientific Reports
- Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
- (2019) Gabriele Campanella et al. NATURE MEDICINE
- Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images
- (2018) Joel Saltz et al. Cell Reports
- Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning
- (2018) Nicolas Coudray et al. NATURE MEDICINE
- Multiple instance learning for histopathological breast cancer image classification
- (2018) P.J. Sudharshan et al. EXPERT SYSTEMS WITH APPLICATIONS
- Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer
- (2017) Babak Ehteshami Bejnordi et al. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
- Comprehensive Computational Pathological Image Analysis Predicts Lung Cancer Prognosis
- (2017) Xin Luo et al. Journal of Thoracic Oncology
- Alectinib versus crizotinib in patients with ALK -positive non-small-cell lung cancer (J-ALEX): an open-label, randomised phase 3 trial
- (2017) Toyoaki Hida et al. LANCET
- A brief introduction to weakly supervised learning
- (2017) Zhi-Hua Zhou National Science Review
- Classifying and segmenting microscopy images with deep multiple instance learning
- (2016) Oren Z. Kraus et al. BIOINFORMATICS
- Image analysis and machine learning in digital pathology: Challenges and opportunities
- (2016) Anant Madabhushi et al. MEDICAL IMAGE ANALYSIS
- Toward a Shared Vision for Cancer Genomic Data
- (2016) Robert L. Grossman et al. NEW ENGLAND JOURNAL OF MEDICINE
- Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis
- (2016) Geert Litjens et al. Scientific Reports
- The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository
- (2013) Kenneth Clark et al. JOURNAL OF DIGITAL IMAGING
- Computational pathology: Challenges and promises for tissue analysis
- (2011) Thomas J. Fuchs et al. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
- Robust Object Tracking with Online Multiple Instance Learning
- (2010) B. Babenko et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started