Search Results for author: Hongfang Liu

Found 28 papers, 4 papers with code

GRU-D-Weibull: A Novel Real-Time Individualized Endpoint Prediction

no code implementations14 Aug 2023 Xiaoyang Ruan, LiWei Wang, Charat Thongprayoon, Wisit Cheungpasitporn, Hongfang Liu

Our findings demonstrate the considerable potential of GRU-D-Weibull as the next-generation architecture for endpoint risk management, capable of generating various endpoint estimates for real-time monitoring using clinical data.


BiomedGPT: A Unified and Generalist Biomedical Generative Pre-trained Transformer for Vision, Language, and Multimodal Tasks

1 code implementation26 May 2023 Kai Zhang, Jun Yu, Zhiling Yan, Yixin Liu, Eashan Adhikarla, Sunyang Fu, Xun Chen, Chen Chen, Yuyin Zhou, Xiang Li, Lifang He, Brian D. Davison, Quanzheng Li, Yong Chen, Hongfang Liu, Lichao Sun

In this paper, we introduce a unified and generalist Biomedical Generative Pre-trained Transformer (BiomedGPT) model, which leverages self-supervision on large and diverse datasets to accept multi-modal inputs and perform a range of downstream tasks.

Image Captioning Medical Visual Question Answering +1

A Cross-institutional Evaluation on Breast Cancer Phenotyping NLP Algorithms on Electronic Health Records

no code implementations15 Mar 2023 Sicheng Zhou, Nan Wang, LiWei Wang, Ju Sun, Anne Blaes, Hongfang Liu, Rui Zhang

We developed three types of NLP models (i. e., conditional random field, bi-directional long short-term memory and CancerBERT) to extract cancer phenotypes from clinical texts.

Detecting Reddit Users with Depression Using a Hybrid Neural Network

no code implementations3 Feb 2023 Ziyi Chen, Ren Yang, Sunyang Fu, Nansu Zong, Hongfang Liu, Ming Huang

In this work, we propose a hybrid deep learning model which combines a pretrained sentence BERT (SBERT) and convolutional neural network (CNN) to detect individuals with depression with their Reddit posts.

text-classification Text Classification

Development of an Extractive Clinical Question Answering Dataset with Multi-Answer and Multi-Focus Questions

no code implementations7 Jan 2022 Sungrim Moon, Huan He, Hongfang Liu, Jungwei W. Fan

Specifically, the 1-to-N, M-to-1, and M-to-N drug-reason relations were included to form the multi-answer and multi-focus QA entries, which represent more complex and natural challenges in addition to the basic one-drug-one-reason cases.

Extractive Question-Answering Question Answering

CancerBERT: a BERT model for Extracting Breast Cancer Phenotypes from Electronic Health Records

no code implementations25 Aug 2021 Sicheng Zhou, LiWei Wang, Nan Wang, Hongfang Liu, Rui Zhang

This data used in the study included 21, 291 breast cancer patients diagnosed from 2010 to 2020, patients' clinical notes and pathology reports were collected from the University of Minnesota Clinical Data Repository (UMN).


An Empirical Study of UMLS Concept Extraction from Clinical Notes using Boolean Combination Ensembles

no code implementations4 Aug 2021 Greg M. Silverman, Raymond L. Finzel, Michael V. Heinz, Jake Vasilakes, Jacob C. Solinsky, Reed McEwan, Benjamin C. Knoll, Christopher J. Tignanelli, Hongfang Liu, Hua Xu, Xiaoqian Jiang, Genevieve B. Melton, Serguei VS Pakhomov

Our objective in this study is to investigate the behavior of Boolean operators on combining annotation output from multiple Natural Language Processing (NLP) systems across multiple corpora and to assess how filtering by aggregation of Unified Medical Language System (UMLS) Metathesaurus concepts affects system performance for Named Entity Recognition (NER) of UMLS concepts.

named-entity-recognition Named Entity Recognition +1

Real space topological invariant and higher-order topological Anderson insulator in two-dimensional non-Hermitian systems

no code implementations24 Feb 2021 Hongfang Liu, Ji-Kun Zhou, Bing-Lan Wu, Zhi-Qiang Zhang, Hua Jiang

We study the characterization and realization of higher-order topological Anderson insulator (HOTAI) in non-Hermitian systems, where the non-Hermitian mechanism ensures extra symmetries as well as gain and loss disorder. We illuminate that the quadrupole moment $Q_{xy}$ can be used as the real space topological invariant of non-Hermitian higher-order topological insulator (HOTI).

Disordered Systems and Neural Networks Mesoscale and Nanoscale Physics

Comparisons of Graph Neural Networks on Cancer Classification Leveraging a Joint of Phenotypic and Genetic Features

no code implementations14 Jan 2021 David Oniani, Chen Wang, Yiqing Zhao, Andrew Wen, Hongfang Liu, Feichen Shen

We applied and compared eight GNN models including AGNN, ChebNet, GAT, GCN, GIN, GraphSAGE, SGC, and TAGCN on the Mayo Clinic cancer disease dataset and assessedtheir performance as well as compared them with each other and with more conventional machinelearning models such as decision tree, gradient boosting, multi-layer perceptron, naive bayes, andrandom forest which we used as the baselines.

Clinical Concept Extraction: a Methodology Review

no code implementations24 Oct 2019 Sunyang Fu, David Chen, Huan He, Sijia Liu, Sungrim Moon, Kevin J Peterson, Feichen Shen, Li-Wei Wang, Yanshan Wang, Andrew Wen, Yiqing Zhao, Sunghwan Sohn, Hongfang Liu

Background Concept extraction, a subdomain of natural language processing (NLP) with a focus on extracting concepts of interest, has been adopted to computationally extract clinical information from text for a wide range of applications ranging from clinical decision support to care quality improvement.

Clinical Concept Extraction Decision Making

How Good is Artificial Intelligence at Automatically Answering Consumer Questions Related to Alzheimer's Disease?

no code implementations21 Aug 2019 Krishna B. Soundararajan, Sunyang Fu, Luke A. Carlson, Rebecca A. Smith, David S. Knopman, Hongfang Liu, Yanshan Wang

The total lifetime cost of care for someone with dementia is estimated to be $350, 174 in 2018, 70% of which is associated with family-provided care.

MedSTS: A Resource for Clinical Semantic Textual Similarity

4 code implementations28 Aug 2018 Yanshan Wang, Naveed Afzal, Sunyang Fu, Li-Wei Wang, Feichen Shen, Majid Rastegar-Mojarad, Hongfang Liu

A subset of MedSTS (MedSTS_ann) containing 1, 068 sentence pairs was annotated by two medical experts with semantic similarity scores of 0-5 (low to high similarity).

Decision Making Semantic Similarity +2

A Comparison of Word Embeddings for the Biomedical Natural Language Processing

2 code implementations1 Feb 2018 Yanshan Wang, Sijia Liu, Naveed Afzal, Majid Rastegar-Mojarad, Li-Wei Wang, Feichen Shen, Paul Kingsbury, Hongfang Liu

First, the word embeddings trained on clinical notes and biomedical publications can capture the semantics of medical terms better, and find more relevant similar medical terms, and are closer to human experts' judgments, compared to these trained on Wikipedia and news.

Information Retrieval

On Developing Resources for Patient-level Information Retrieval

no code implementations LREC 2016 Stephen Wu, Tamara Timmons, Amy Yates, Meikun Wang, Steven Bedrick, William Hersh, Hongfang Liu

Privacy concerns have often served as an insurmountable barrier for the production of research and resources in clinical information retrieval (IR).

Information Retrieval Retrieval

Staggered NLP-assisted refinement for Clinical Annotations of Chronic Disease Events

no code implementations LREC 2016 Stephen Wu, Chung-Il Wi, Sunghwan Sohn, Hongfang Liu, Young Juhn

Domain-specific annotations for NLP are often centered on real-world applications of text, and incorrect annotations may be particularly unacceptable.

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