Deep Learning On Medical Research本论文集收集了医疗领域结合AI深度学习的实际应用和理论的相关论文
Hei Law,Jia Deng
International Journal of Computer Vision, no. 3 (2019): 642-656
In this paper we introduce CornerNet, a new one-stage approach to object detection that does away with anchor boxes
Cited by403BibtexViews133Links
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ICLR, (2019)
The Universal Transformer combines the following key properties into one model: Weight sharing: Following intuitions behind weight sharing found in CNNs and recurrent neural networks, we extend the Transformer with a simple form of weight sharing that strikes an effective balance...
Cited by207BibtexViews298Links
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ICLR, (2019)
We empirically show that the global and the local memory pointer are able to effectively produce system responses even in the out-of-vocabulary scenario, and visualize how global memory pointer helps as well
Cited by44BibtexViews59Links
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arXiv: Computation and Language, (2019): 16-28
Model analysis shows that our system could discover useful evidence from commonsense knowledge base
Cited by16BibtexViews90Links
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Suman Banerjee,Mitesh M. Khapra
TACL, (2019): 485-500
We empirically showed that when dependency parsers are not available for certain languages such as code-mixed languages we can use word co-occurrence frequencies and positive-pointwise mutual information values to extract a contextual graph and use such a graph with Graph Convolu...
Cited by1BibtexViews30Links
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north american chapter of the association for computational linguistics, (2018)
Recent empirical improvements due to transfer learning with language models have demonstrated that rich, unsupervised pre-training is an integral part of many language understanding systems
Cited by7048BibtexViews1127Links
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international conference on learning representations, (2018)
We achieve state-of-the-art results on multiple benchmark knowledge base completion tasks and we show that our model is robust and can learn long chains-ofreasoning
Cited by157BibtexViews365Links
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Journal of medical imaging (Bellingham, Wash.), no. 3 (2018): 036501
Categorize and detect one type of clinical annotations stored in the hospital Picture Archiving and Communication Systems system as a rich retrospective data source, to build a large-scale Radiology lesion image database
Cited by124BibtexViews28Links
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meeting of the association for computational linguistics, (2018)
We study how to automatically generate textual reports for medical images, with the goal to help medical professionals produce reports more accurately and efficiently
Cited by98BibtexViews59Links
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north american chapter of the association for computational linguistics, (2018): 708-719
Our proposed measures and the analysis of strategies used by different publications and articles propose new directions for evaluating the difficulty of summarization tasks and for developing future summarization models
Cited by90BibtexViews108Links
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ACL, pp.1736-1745, (2018)
We propose a denoising distantly supervised open-domain question answering system which contains a paragraph selector to skim over paragraphs and a paragraph reader to perform an intensive reading on the selected paragraphs
Cited by79BibtexViews74Links
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computer vision and pattern recognition, (2018)
Like web data in computer vision, a vast, loosely-labeled, and largely untapped data source does exist in the form of hospital picture archiving and communication systems
Cited by63BibtexViews39Links
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ACL, pp.1489-1498, (2018)
We identify the knowledge diffusion in conversations and propose an end-to-end neural knowledge diffusion model to deal with the problem
Cited by61BibtexViews34Links
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Ke Yan, Mohammadhadi Bagheri,Ronald M. Summers
MICCAI, (2018)
We presented 3D context enhanced region-based convolutional neural networks to leverage the 3D context when detecting lesions in volumetric data. 3D context enhanced region-based CNN is
Cited by46BibtexViews25Links
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arXiv: Computation and Language, (2018)
Some SQuAD 2.0 questions are unlikely to be asked without significant foreknowledge of the context material and do not occur in QuAC. 4 Both SQuAD 2.0 and QuAC cover a significant number of unanswerable questions that could be plausibly in the article
Cited by41BibtexViews29Links
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arXiv: Computation and Language, (2018)
Results show that the three types of edges are useful on combining global evidence and that the graph neural networks are effective on encoding complex graphs resulted by the first step
Cited by40BibtexViews87Links
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Zhongyu Wei, Qianlong Liu,Baolin Peng, Huaixiao Tou,Ting Chen,Xuanjing Huang,Kam-Fai Wong, Xiangying Dai
ACL, pp.201-207, (2018)
We focus on the Dialogue Manager for automatic diagnosis consisting of two sub-modules, namely, dialogue state tracker and policy learning
Cited by38BibtexViews59Links
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EMNLP, (2018): 2087-2097
Annotators show substantial agreement when constructing dialogs with a three-way annotator agreement at a Fleiss’ Kappa level of 0.71.1 Likewise, we find that
Cited by36BibtexViews67Links
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Yansen Wang, Chenyi Liu,Minlie Huang,Liqiang Nie
meeting of the association for computational linguistics, (2018)
We presented error type distribution by manually analyzing 100 bad responses sampled from Soft Typed Decoder and Hard Typed Decoder respectively, where bad means the response by our model is worse than that by some baseline during the pair-wise annotation
Cited by33BibtexViews47Links
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CVPR, (2018): 7736-7745
We present the Visual Knowledge Memory Network method as an efficient way to leverage pre-built visual knowledge base for accurate visual question answering
Cited by23BibtexViews81Links
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Keywords
Associative EmbeddingBookmarkConvolutional Neural NetworkDeep LearningHourglass NetworkLesion DetectionMedical Image DatasetObject DetectionPicture Archiving And Communication System
Authors
Ronald M. Summers
Paper 3
Ke Yan
Paper 3
Percy Liang
Paper 2
Xiaodan Zhu
Paper 2
Jianfeng Gao
Paper 2
Bhuwan Dhingra
Paper 2
He He
Paper 2
Yun-Nung Chen
Paper 2
Zhenhua Ling
Paper 2
Qian Chen
Paper 2