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第1回 : Automatic Diagnosis Coding of Radiology Reports: A Comparison of Deep Learning and Conventional Classification Methods [paper]  [slide]
第2回 : A Machine Learning Approach to Clinical Terms Normalization [paper] [slide(Speaker Deck)]
第3回 : DOC: Deep Open Classification of Text Documents [paper] [slide(Speaker Deck)]
第4回 : Joint Embedding of Words and Labels for Text Classification [paper] [slide(Speaker Deck)]
第5回 : SCDV: Sparse Composite Document Vectors using soft clustering over distributional representations [paper] [slide(Speaker Deck)]
第6回 : How to Train good Word Embeddings for Biomedical NLP [paper] [slide(Speaker Deck)]
第7回 : An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generation [paper] [slide(Speaker Deck)]
第8回 : Learning and Evaluating Sparse Interpretable Sentence Embeddings [paper] [slide(Speaker Deck)]
第9回 : On Learning Better Word Embeddings from Chinese Clinical Records: Study on Combining In-Domain and Out-Domain Data [paper] [slide(Speaker Deck)]
第10回 : Learning to Summarize Radiology Findings [paper] [slide(Speaker Deck)]
第11回 : Effectively Crowdsourcing Radiology Report Annotations [paper] [slide(Speaker Deck)]
第12回 : Exploring Semantic Properties of Sentence Embeddings [paper] [slide(Speaker Deck)]
第13回 : Biomedical Document Retrieval for Clinical Decision Support System [paper] [slide(Speaker Deck)]
第14回 : Context-Aware Cross-Lingual Mapping [paper] [slide(Speaker Deck)]
第15回 : Predicting Annotation Difficulty to Improve Task Routing and Model Performance for Biomedical Information Extraction [paper] [slide(Speaker Deck)]
第16回 : Is Word Segmentation Necessary for Deep Learning of Chinese Representations? [paper] [slide(Speaker Deck)]
第17回 : Medical Word Embeddings for Spanish: Development and Evaluation [paper] [slide(Speaker Deck)]
第18回 : Sentence Mover’s Similarity: Automatic Evaluation for Multi-Sentence Texts [paper] [slide(Speaker Deck)]
第19回 : Do Neural NLP Models Know Numbers? Probing Numeracy in Embeddings [paper] [slide(Speaker Deck)]
    ※arxivではタイトルが Do NLP Models Know Numbers? Probing Numeracy in Embeddings(2019/10/27現在)
第20回 : EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks [paper] [slide(Speaker Deck)]
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