726 citations · 2.2k across the 66 of their papers we have counts for
12 papers · 1 filter
Type Information Utilized Event Detection via Multi-Channel GNNs in Electrical Power Systems
Qian Li, Jianxin Li, Lihong Wang +6
Event detection in power systems aims to identify triggers and event types, which helps relevant personnel respond to emergencies promptly and facilitates the optimization of power…
Self-supervised Regularization for Text Classification
Meng Zhou, Zechen Li, Pengtao Xie
Text classification is a widely studied problem and has broad applications. In many real-world problems, the number of texts for training classification models is limited, which re…
CERT: Contrastive Self-supervised Learning for Language Understanding
Hongchao Fang, Sicheng Wang, Meng Zhou +2
Pretrained language models such as BERT, GPT have shown great effectiveness in language understanding. The auxiliary predictive tasks in existing pretraining approaches are mostly…
On the Generation of Medical Dialogues for COVID-19
Wenmian Yang, Guangtao Zeng, Bowen Tan +9
Under the pandemic of COVID-19, people experiencing COVID19-related symptoms or exposed to risk factors have a pressing need to consult doctors. Due to hospital closure, a lot of c…
PathVQA: 30000+ Questions for Medical Visual Question Answering
Xuehai He, Yichen Zhang, Luntian Mou +2
Is it possible to develop an "AI Pathologist" to pass the board-certified examination of the American Board of Pathology? To achieve this goal, the first step is to create a visual…
Generalized Zero-shot ICD Coding
Congzheng Song, Shanghang Zhang, Najmeh Sadoughi +2
The International Classification of Diseases (ICD) is a list of classification codes for the diagnoses. Automatic ICD coding is in high demand as the manual coding can be labor-int…
Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Records
Xiangan Liu, Keyang Xu, Pengtao Xie +1
Extractive summarization is very useful for physicians to better manage and digest Electronic Health Records (EHRs). However, the training of a supervised model requires disease-sp…
Convolutional Neural Networks for Medical Diagnosis from Admission Notes
Christy Li, Dimitris Konomis, Graham Neubig +3
Develop an automatic diagnostic system which only uses textual admission information from Electronic Health Records (EHRs) and assist clinicians with a timely…
Predicting Discharge Medications at Admission Time Based on Deep Learning
Yuan Yang, Pengtao Xie, Xin Gao +4
Predicting discharge medications right after a patient being admitted is an important clinical decision, which provides physicians with guidance on what type of medication regimen…
Towards Automated ICD Coding Using Deep Learning
Haoran Shi, Pengtao Xie, Zhiting Hu +2
International Classification of Diseases(ICD) is an authoritative health care classification system of different diseases and conditions for clinical and management purposes. Consi…
On the Automatic Generation of Medical Imaging Reports
Baoyu Jing, Pengtao Xie, Eric Xing
Medical imaging is widely used in clinical practice for diagnosis and treatment. Report-writing can be error-prone for unexperienced physicians, and time- consuming and tedious for…
Effective Use of Bidirectional Language Modeling for Transfer Learning in Biomedical Named Entity Recognition
Devendra Singh Sachan, Pengtao Xie, Mrinmaya Sachan +1
Biomedical named entity recognition (NER) is a fundamental task in text mining of medical documents and has many applications. Deep learning based approaches to this task have been…