Adaptive adversarial neural networks for the analysis of lossy and domain-shifted datasets of medical images
出版年份 2021 全文链接
标题
Adaptive adversarial neural networks for the analysis of lossy and domain-shifted datasets of medical images
作者
关键词
-
出版物
Nature Biomedical Engineering
Volume -, Issue -, Pages -
出版商
Springer Science and Business Media LLC
发表日期
2021-06-11
DOI
10.1038/s41551-021-00733-w
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。- Consistency and objectivity of automated embryo assessments using deep neural networks
- (2020) Charles L. Bormann et al. FERTILITY AND STERILITY
- GANs for Medical Image Analysis
- (2020) Salome Kazeminia et al. ARTIFICIAL INTELLIGENCE IN MEDICINE
- A Survey of Unsupervised Deep Domain Adaptation
- (2020) Garrett Wilson et al. ACM Transactions on Intelligent Systems and Technology
- Performance of a deep learning based neural network in the selection of human blastocysts for implantation
- (2020) Charles L Bormann et al. eLife
- Taking connected mobile-health diagnostics of infectious diseases to the field
- (2019) Christopher S. Wood et al. NATURE
- Artificial intelligence and machine learning for human reproduction and embryology presented at ASRM and ESHRE 2018
- (2019) Carol Lynn Curchoe et al. JOURNAL OF ASSISTED REPRODUCTION AND GENETICS
- Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning
- (2019) Yair Rivenson et al. Nature Biomedical Engineering
- Applications, promises, and pitfalls of deep learning for fluorescence image reconstruction
- (2019) Chinmay Belthangady et al. NATURE METHODS
- Human sperm morphology analysis using smartphone microscopy and deep learning
- (2019) Prudhvi Thirumalaraju et al. FERTILITY AND STERILITY
- Association Between Surgical Skin Markings in Dermoscopic Images and Diagnostic Performance of a Deep Learning Convolutional Neural Network for Melanoma Recognition
- (2019) Julia K. Winkler et al. JAMA Dermatology
- Deep learning in holography and coherent imaging
- (2019) Yair Rivenson et al. Light-Science & Applications
- Key challenges for delivering clinical impact with artificial intelligence
- (2019) Christopher J. Kelly et al. BMC Medicine
- Artificial intelligence for global health
- (2019) Ahmed Hosny et al. SCIENCE
- Image analysis and machine learning for detecting malaria
- (2018) Mahdieh Poostchi et al. Translational Research
- Deep Learning Enhanced Mobile-Phone Microscopy
- (2018) Yair Rivenson et al. ACS Photonics
- Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images
- (2018) Sivaramakrishnan Rajaraman et al. PeerJ
- Automated sperm morpshology testing using artificial intelligence
- (2018) P. Thirumalaraju et al. FERTILITY AND STERILITY
- Home sperm testing device versus laboratory sperm quality analyzer: comparison of motile sperm concentration
- (2018) Ashok Agarwal et al. FERTILITY AND STERILITY
- A guide to deep learning in healthcare
- (2018) Andre Esteva et al. NATURE MEDICINE
- High-performance medicine: the convergence of human and artificial intelligence
- (2018) Eric J. Topol NATURE MEDICINE
- Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: A cross-sectional study
- (2018) John R. Zech et al. PLOS MEDICINE
- An automated smartphone-based diagnostic assay for point-of-care semen analysis
- (2017) Manoj Kumar Kanakasabapathy et al. Science Translational Medicine
- The future of computer-aided sperm analysis
- (2015) David Mortimer et al. ASIAN JOURNAL OF ANDROLOGY
- Deep learning
- (2015) Yann LeCun et al. NATURE
- The blastocyst
- (2012) T. Hardarson et al. HUMAN REPRODUCTION
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now