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20172020
most citedPublicly Available Clinical BERT Embeddings

732 citations · 934 across the 9 of their papers we have counts for

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7 papers · 1 filter

cs.CL202064 cited

What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams

Di Jin, Eileen Pan, Nassim Oufattole +3

Open domain question answering (OpenQA) tasks have been recently attracting more and more attention from the natural language processing (NLP) community. In this work, we present t…

cs.CL20208 cited

Clinical Text Summarization with Syntax-Based Negation and Semantic Concept Identification

Wei-Hung Weng, Yu-An Chung, Schrasing Tong

In the era of clinical information explosion, a good strategy for clinical text summarization is helpful to improve the clinical workflow. The ideal summarization strategy can pres…

cs.CL20192 cited

Human-centric Metric for Accelerating Pathology Reports Annotation

Ruibin Ma, Po-Hsuan Cameron Chen, Gang Li +4

Pathology reports contain useful information such as the main involved organ, diagnosis, etc. These information can be identified from the free text reports and used for large-scal…

cs.CL2019732 cited

Publicly Available Clinical BERT Embeddings

Emily Alsentzer, John R. Murphy, Willie Boag +4

Contextual word embedding models such as ELMo (Peters et al., 2018) and BERT (Devlin et al., 2018) have dramatically improved performance for many natural language processing (NLP)…

cs.CL2019

Unsupervised Clinical Language Translation

Wei-Hung Weng, Yu-An Chung, Peter Szolovits

As patients' access to their doctors' clinical notes becomes common, translating professional, clinical jargon to layperson-understandable language is essential to improve patient-…

cs.CL2018

Towards Unsupervised Speech-to-Text Translation

Yu-An Chung, Wei-Hung Weng, Schrasing Tong +1

We present a framework for building speech-to-text translation (ST) systems using only monolingual speech and text corpora, in other words, speech utterances from a source language…