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20162022
most citedOnline User Profiling to Detect Social Bots on Twitter

18 citations · 32 across the 5 of their papers we have counts for

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6 papers · 1 filter

cs.CL20213 cited

Extracting Radiological Findings With Normalized Anatomical Information Using a Span-Based BERT Relation Extraction Model

Kevin Lybarger, Aashka Damani, Martin Gunn +2

Medical imaging is critical to the diagnosis and treatment of numerous medical problems, including many forms of cancer. Medical imaging reports distill the findings and observatio…

cs.CL20211 cited

Performance of Automatic De-identification Across Different Note Types

Nicholas Dobbins, David Wayne, Kahyun Lee +2

Free-text clinical notes detail all aspects of patient care and have great potential to facilitate quality improvement and assurance initiatives as well as advance clinical researc…

cs.CL2021

A Context-Enhanced De-identification System

Kahyun Lee, Mehmet Kayaalp, Sam Henry +1

Many modern entity recognition systems, including the current state-of-the-art de-identification systems, are based on bidirectional long short-term memory (biLSTM) units augmented…

cs.CL202110 cited

Transfer Learning Approach for Arabic Offensive Language Detection System -- BERT-Based Model

Fatemah Husain, Ozlem Uzuner

Developing a system to detect online offensive language is very important to the health and the security of online users. Studies have shown that cyberhate, online harassment and o…

cs.CL2021

Exploratory Arabic Offensive Language Dataset Analysis

Fatemah Husain, Ozlem Uzuner

This paper adding more insights towards resources and datasets used in Arabic offensive language research. The main goal of this paper is to guide researchers in Arabic offensive l…

cs.CL2016

De-identification of Patient Notes with Recurrent Neural Networks

Franck Dernoncourt, Ji Young Lee, Ozlem Uzuner +1

Objective: Patient notes in electronic health records (EHRs) may contain critical information for medical investigations. However, the vast majority of medical investigators can on…