activity
20172022
most citedNegBio: a high-performance tool for negation and uncertainty detection in radiology reports

129 citations · 290 across the 14 of their papers we have counts for

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Showing cs.CLShow all

8 papers · 1 filter

cs.CL20221 cited

Classifying Cyber-Risky Clinical Notes by Employing Natural Language Processing

Suzanna Schmeelk, Martins Samuel Dogo, Yifan Peng +1

Clinical notes, which can be embedded into electronic medical records, document patient care delivery and summarize interactions between healthcare providers and patients. These cl…

cs.CL2022

Radiology Text Analysis System (RadText): Architecture and Evaluation

Song Wang, Mingquan Lin, Ying Ding +3

Analyzing radiology reports is a time-consuming and error-prone task, which raises the need for an efficient automated radiology report analysis system to alleviate the workloads o…

cs.CL202012 cited

An Empirical Study of Multi-Task Learning on BERT for Biomedical Text Mining

Yifan Peng, Qingyu Chen, Zhiyong Lu

Multi-task learning (MTL) has achieved remarkable success in natural language processing applications. In this work, we study a multi-task learning model with multiple decoders on…

cs.CL201972 cited

Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets

Yifan Peng, Shankai Yan, Zhiyong Lu

Inspired by the success of the General Language Understanding Evaluation benchmark, we introduce the Biomedical Language Understanding Evaluation (BLUE) benchmark to facilitate res…

cs.CL20192 cited

A self-attention based deep learning method for lesion attribute detection from CT reports

Yifan Peng, Ke Yan, Veit Sandfort +2

In radiology, radiologists not only detect lesions from the medical image, but also describe them with various attributes such as their type, location, size, shape, and intensity.…

cs.CL2018

BioSentVec: creating sentence embeddings for biomedical texts

Qingyu Chen, Yifan Peng, Zhiyong Lu

Sentence embeddings have become an essential part of today's natural language processing (NLP) systems, especially together advanced deep learning methods. Although pre-trained sen…