Carsten Eickhoff

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Brown University ∙ Association for Computing Machinery ∙ ETH Zurich

Diagnosis Prevalence vs. Efficacy in Machine-learning Based Diagnostic Decision Support

Many recent studies use machine learning to predict a small number of IC...
06/24/2020 ∙ by Gil Alon, et al. ∙ 0 ∙ share

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Mining Misdiagnosis Patterns from Biomedical Literature

Diagnostic errors can pose a serious threat to patient safety, leading t...
06/24/2020 ∙ by Cindy Li, et al. ∙ 0 ∙ share

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Wasserstein Adversarial Autoencoders for Knowledge Graph Embedding based Drug-Drug Interaction Prediction

Interaction between pharmacological agents can trigger unexpected advers...
04/15/2020 ∙ by Yuanfei Dai, et al. ∙ 7 ∙ share

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DC3 – A Diagnostic Case Challenge Collection for Clinical Decision Support

In clinical care, obtaining a correct diagnosis is the first step toward...
08/22/2019 ∙ by Carsten Eickhoff, et al. ∙ 0 ∙ share

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Embedding Electronic Health Records for Clinical Information Retrieval

Neural network representation learning frameworks have recently shown to...
11/13/2018 ∙ by Xing Wei, et al. ∙ 0 ∙ share

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Biomedical Question Answering via Weighted Neural Network Passage Retrieval

The amount of publicly available biomedical literature has been growing ...
01/09/2018 ∙ by Ferenc Galkó, et al. ∙ 0 ∙ share

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Web2Text: Deep Structured Boilerplate Removal

Web pages are a valuable source of information for many natural language...
01/08/2018 ∙ by Thijs Vogels, et al. ∙ 0 ∙ share

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Evaluating Music Recommender Systems for Groups

Recommendation to groups of users is a challenging and currently only pa...
07/31/2017 ∙ by Zsolt Mezei, et al. ∙ 0 ∙ share

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Neural Document Embeddings for Intensive Care Patient Mortality Prediction

We present an automatic mortality prediction scheme based on the unstruc...
12/01/2016 ∙ by Paulina Grnarova, et al. ∙ 0 ∙ share

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Efficient Parallel Learning of Word2Vec

Since its introduction, Word2Vec and its variants are widely used to lea...
06/24/2016 ∙ by Jeroen B. P. Vuurens, et al. ∙ 0 ∙ share

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Computing Web-scale Topic Models using an Asynchronous Parameter Server

Topic models such as Latent Dirichlet Allocation (LDA) have been widely ...
05/24/2016 ∙ by Rolf Jagerman, et al. ∙ 0 ∙ share

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Probabilistic Bag-Of-Hyperlinks Model for Entity Linking

Many fundamental problems in natural language processing rely on determi...
09/08/2015 ∙ by Octavian-Eugen Ganea, et al. ∙ 0 ∙ share

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Carsten Eickhoff

Featured Co-authors

Maarten de Rijke

Thomas Hofmann

Aurelien Lucchi

Octavian-Eugen Ganea

Florian Schmidt

Xing Wei

Stephanie L. Hyland

Rolf Jagerman

Arjen P. de Vries

Paulina Grnarova

Wenzhong Guo

Diagnosis Prevalence vs. Efficacy in Machine-learning Based Diagnostic Decision Support

Mining Misdiagnosis Patterns from Biomedical Literature

Wasserstein Adversarial Autoencoders for Knowledge Graph Embedding based Drug-Drug Interaction Prediction

DC3 – A Diagnostic Case Challenge Collection for Clinical Decision Support

Embedding Electronic Health Records for Clinical Information Retrieval

Biomedical Question Answering via Weighted Neural Network Passage Retrieval

Web2Text: Deep Structured Boilerplate Removal

Evaluating Music Recommender Systems for Groups

Neural Document Embeddings for Intensive Care Patient Mortality Prediction

Efficient Parallel Learning of Word2Vec

Computing Web-scale Topic Models using an Asynchronous Parameter Server

Probabilistic Bag-Of-Hyperlinks Model for Entity Linking