Filters








836 Hits in 6.1 sec

PASCAL: a pseudo cascade learning framework for breast cancer treatment entity normalization in Chinese clinical text

Yang An, Jianlin Wang, Liang Zhang, Hanyu Zhao, Zhan Gao, Haitao Huang, Zhenguang Du, Zengtao Jiao, Jun Yan, Xiaopeng Wei, Bo Jin
2020 BMC Medical Informatics and Decision Making  
In addition, despite its importance in clinical and translational research, few studies directly deal with the normalization task in Chinese clinical text due to the complexity of composition forms.  ...  Finally, by concatenating the context-aware vector and probabilistic distribution vector from TEN, we utilize the conditional random field layer (CRF) to model the normalization sequence and predict the  ...  Acknowledgments The authors would like to thank the editor and all anonymous reviewers for valuable suggestions and constructive comments. We thank the Yidu Cloud for providing a research platform. 1  ... 
doi:10.1186/s12911-020-01216-9 pmid:32859189 fatcat:ywmonkkuevfi5llwgktwn3cd4a

Ontologies, Knowledge Representation, and Machine Learning for Translational Research: Recent Contributions

Peter N. Robinson, Melissa A. Haendel
2020 IMIA Yearbook of Medical Informatics  
algorithms to supplement natural language processing (NLP) of EHRs and other medical texts; and (iii) hybrid ontology and NLP-based approaches to extracting structured and unstructured components of EHRs  ...  The chosen articles belong to three major themes: (i) the identification of phenotypic abnormalities in electronic health record (EHR) data using the Human Phenotype Ontology ; (ii) word and node embedding  ...  Acknowledgements The authors were supported by a grant from the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR00230.  ... 
doi:10.1055/s-0040-1701991 pmid:32823310 fatcat:pbi3fv2cmzhcjjdmgxun6omyfu

Knowledge-based Biomedical Data Science 2019 [article]

Tiffany J. Callahan, Ignacio J. Tripodi Computational Bioscience Program, Department of Pharmacology, University of Colorado Denver Anschutz Medical Campus
2019 arXiv   pre-print
Major themes include the relationships between knowledge graphs and machine learning, the use of natural language processing, and the expansion of knowledge-based approaches to novel domains, such as Chinese  ...  Here we survey the progress in the last year in systems that use formally represented knowledge to address data science problems in both clinical and biological domains, as well as on approaches for creating  ...  To improve the identification of comorbid diseases, Biswas, Mitra & Rao (37) built a KG using the approach outlined by (36) and then performed link prediction using an inductive inference method.  ... 
arXiv:1910.06710v1 fatcat:kvz5k643zvhpdiq67blc2v33wi

SECNLP: A Survey of Embeddings in Clinical Natural Language Processing [article]

Kalyan KS, S Sangeetha
2019 arXiv   pre-print
In this survey paper, we discuss various medical corpora and their characteristics, medical codes and present a brief overview as well as comparison of popular embeddings models.  ...  We discuss various evaluation methods followed by possible solutions to various challenges in clinical embeddings.  ...  Character and word embeddings are generated using word2vec and Chinese medical corpora, sentence embeddings using Bi-LSTM.  ... 
arXiv:1903.01039v3 fatcat:5d6lhm2x3zc3rbhfoefzqtngp4

Framing Electronic Medical Records as Polylingual Documents in Query Expansion

Edward W Huang, Sheng Wang, Doris Jung-Lin Lee, Runshun Zhang, Baoyan Liu, Xuezhong Zhou, ChengXiang Zhai
2018 AMIA Annual Symposium Proceedings  
These baselines include methods used in prior studies as well as state-of-the-art embedding techniques.  ...  However, due to semantic, functional, and treatment synonyms in medical terminology, queries are often incomplete and thus require enhancement.  ...  by State Administration of Traditional Chinese Medicine grant 201407001.  ... 
pmid:29854161 pmcid:PMC5977599 fatcat:jokey77pyvathh33ymicz2c3xa

Machine Learning Based Sentiment Text Classification for Evaluating Treatment Quality of Discharge Summary

Samer Abdulateef Waheeb, Naseer Ahmed Khan, Bolin Chen, Xuequn Shang
2020 Information  
Patients' discharge summaries (documents) are health sensors that are used for measuring the quality of treatment in medical centers.  ...  These kinds of documents include various aspects of patient information that could be used to test the treatment quality for improving medical-related decisions.  ...  Acknowledgments: We are very grateful to Chinese Scholarship Council scholarship (CSC) for providing us financial and moral support.  ... 
doi:10.3390/info11050281 fatcat:popbihfkl5d73i26bvbikawsvy

Capturing the Patient's Perspective: a Review of Advances in Natural Language Processing of Health-Related Text

G. Gonzalez-Hernandez, A. Sarker, K. O'Connor, G. Savova
2017 IMIA Yearbook of Medical Informatics  
Effective mechanisms to filter out noise and for mapping social media expressions to standard medical concepts are crucial and latent research problems.  ...  Recent advances in noisy text processing techniques are enabling researchers and medical domain experts to go beyond the information encapsulated in published texts (e.g., clinical trials and systematic  ...  Acknowledgments The authors are partially supported by funding from the US National Institutes of Health (1U24CA184407-01, R01LM10090, R01GM114355).  ... 
doi:10.15265/iy-2017-029 pmid:29063568 pmcid:PMC6250990 fatcat:i6kvjcddgnbfvojmloral5pncu

Capturing the Patient's Perspective: a Review of Advances in Natural Language Processing of Health-Related Text

G. Gonzalez-Hernandez, A. Sarker, K. O'Connor, G. Savova
2017 IMIA Yearbook of Medical Informatics  
Effective mechanisms to filter out noise and for mapping social media expressions to standard medical concepts are crucial and latent research problems.  ...  Recent advances in noisy text processing techniques are enabling researchers and medical domain experts to go beyond the information encapsulated in published texts (e.g., clinical trials and systematic  ...  Acknowledgments The authors are partially supported by funding from the US National Institutes of Health (1U24CA184407-01, R01LM10090, R01GM114355).  ... 
doi:10.1055/s-0037-1606506 fatcat:ujcstkryrzhgpalibaaduzchfy

Artificial Intelligence (AI) in Action: Addressing the COVID-19 Pandemic with Natural Language Processing (NLP) [article]

Qingyu Chen, Robert Leaman, Alexis Allot, Ling Luo, Chih-Hsuan Wei, Shankai Yan, Zhiyong Lu
2021 arXiv   pre-print
We conclude by discussing observable trends and remaining challenges.  ...  Natural language processing (NLP), the branch of artificial intelligence that interprets human language, can be applied to address many of the information needs made urgent by the COVID-19 pandemic.  ...  Acknowledgement This research is supported by the NIH Intramural Research Program, National Library of Medicine. Literature Cited  ... 
arXiv:2010.16413v2 fatcat:cxzxmnnbfrednpto4zkpnemltm

Artificial Intelligence in Action: Addressing the COVID-19 Pandemic with Natural Language Processing

Qingyu Chen, Robert Leaman, Alexis Allot, Ling Luo, Chih-Hsuan Wei, Shankai Yan, Zhiyong Lu
2021 Annual Review of Biomedical Data Science  
We conclude by discussing observable trends and remaining challenges. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 4 is July 2021.  ...  Natural language processing (NLP)—the branch of artificial intelligence that interprets human language—can be applied to address many of the information needs made urgent by the COVID-19 pandemic.  ...  ACKNOWLEDGMENTS This research is supported by the NIH Intramural Research Program, National Library of Medicine.  ... 
doi:10.1146/annurev-biodatasci-021821-061045 pmid:34465169 fatcat:gxtcwu5ih5gx3la6ea4674pnmu

Information Needs of Breast Cancer Patients: Theory-Generating Meta-Synthesis

Hongru Lu, Juan Xie, Lynette Hammond Gerido, Ying Cheng, Ya Chen, Lizhu Sun
2020 Journal of Medical Internet Research  
Data analysis was guided by the theory-generating meta-synthesis and grounded theory approach.  ...  A Google Scholar search, interpersonal network recommendations, and reference chaining were also conducted.  ...  First, four authors (HL, JX, Y Cheng, and LS) identified the concepts that best fit the extracted raw texts.  ... 
doi:10.2196/17907 pmid:32720899 fatcat:kk3crooapvgmhn5x7aztdw6try

NiaoDuQing granules relieve chronic kidney disease symptoms by decreasing renal fibrosis and anemia

Xu Wang, Suyun Yu, Qi Jia, Lichuan Chen, Jinqiu Zhong, Yanhong Pan, Peiliang Shen, Yin Shen, Siliang Wang, Zhonghong Wei, Yuzhu Cao, Yin Lu
2017 OncoTarget  
Experimental results confirmed that NDQ granules exerted therapeutic effects on CKD and its comorbidities, including renal anemia, mainly by modulating the TGF-β and EPO signaling pathways.  ...  NiaoDuQing (NDQ) granules, a traditional Chinese medicine, has been clinically used in China for over fourteen years to treat chronic kidney disease (CKD).  ...  This database is established based on Chinese scientific publications and medical texts, containing over 13731 pure compounds isolated from 505 TCM herbs.  ... 
doi:10.18632/oncotarget.18473 pmid:28915563 pmcid:PMC5593534 fatcat:7fifkllfjrfavoi7vgzqvg2hhi

Data Harmonization for Heterogeneous Datasets: A Systematic Literature Review

Ganesh Kumar, Shuib Basri, Abdullahi Abubakar Imam, Sunder Ali Khowaja, Luiz Fernando Capretz, Abdullateef Oluwagbemiga Balogun
2021 Applied Sciences  
The result shows that the heterogeneity of structured, semi-structured, and unstructured (SSU) data can be managed by using DH and its core techniques, such as text preprocessing, Natural Language Preprocessing  ...  Lastly, we present readers with a detailed discussion of the existing work, contributions, and managerial and academic implications, along with the conclusion, limitations, and future research directions  ...  integration and semantic-based medical retrieval Clinical records without linguistic standard [3] General Purpose Heterogeneous data can be solved by using RDBMS,concept lattice, and MapReduce Performance  ... 
doi:10.3390/app11178275 fatcat:2e5jcmsodrej3fwkxkftiwhrsu

Latent Dirichlet Allocation (LDA) and Topic modeling: models, applications, a survey [article]

Hamed Jelodar, Yongli Wang, Chi Yuan, Xia Feng, Xiahui Jiang, Yanchao Li, Liang Zhao
2018 arXiv   pre-print
Topic modeling is one of the most powerful techniques in text mining for data mining, latent data discovery, and finding relationships among data, text documents.  ...  According to previous work, this paper can be very useful and valuable for introducing LDA approaches in topic modeling.  ...  30916011328, 30918015103), and Nanjing Science and Technology Development Plan Project (201805036).  ... 
arXiv:1711.04305v2 fatcat:jzsx6owjyjfo3gkbohrc2ggkzq

Healthcare Knowledge Graph Construction: State-of-the-art, open issues, and opportunities [article]

Bilal Abu-Salih, Muhammad AL-Qurishi, Mohammed Alweshah, Mohammad AL-Smadi, Reem Alfayez, Heba Saadeh
2022 arXiv   pre-print
These techniques are critically evaluated in terms of methods used for knowledge extraction, types of the knowledge base and sources, and the incorporated evaluation protocols.  ...  The incorporation of data analytics in the healthcare industry has made significant progress, driven by the demand for efficient and effective big data analytics solutions.  ...  Another Chinese medical KG was proposed by [130] .  ... 
arXiv:2207.03771v1 fatcat:r5y3hjqvrfd4xc6exje6lcngj4
« Previous Showing results 1 — 15 out of 836 results