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Trie-based rule processing for clinical NLP: A use-case study of n-trie, making the ConText algorithm more efficient and scalable

Jianlin Shi, John F. Hurdle
2018 Journal of Biomedical Informatics  
Background: The ConText algorithm performs with state-of-art accuracy in detecting the experiencer, negation status, and temporality of concept mentions in clinical narratives.  ...  However, the speed limitation of its current implementations hinders its use in big data processing.  ...  Neither sponsor played a role in the design of the study nor in data collection, analysis, or interpretation.  ... 
doi:10.1016/j.jbi.2018.08.002 pmid:30092358 pmcid:PMC6171746 fatcat:llcevuoqhndavcy2xozkyogqdq

Comparison of MetaMap, cTAKES, SIFR, and ECMT to Annotate Breast Cancer Patient Summaries [chapter]

Akram Redjdal, Jacques Bouaud, Joseph Gligorov, Brigitte Séroussi
2022 Studies in Health Technology and Informatics  
We compared the four annotators on a sample of 25 French BCPSs, pre-processed to manage acronyms and translated in English.  ...  Annotators have been developed to extract the relevant content of such documents, e.g., MetaMap and cTAKES, that work with the English language and perform concept mapping using UMLS, SIFR and ECMT, that  ...  Acknowledgements The authors thank the University Institute of Health Engineering (IUIS -Sorbonne University) for financing this research and the AP-HP health data warehouse for supporting this work.  ... 
doi:10.3233/shti220058 pmid:35672997 fatcat:p6rlxisom5fopidydj33ui7wfa

DiiS: A Biomedical Data Access Framework for Aiding Data Driven Research Supporting FAIR Principles

Priya Deshpande, Alexander Rasin, Jacob Furst, Daniela Raicu, Sameer Antani
2019 Data  
Vast amounts of clinical and biomedical research data are produced daily.  ...  Our research work describes the challenges inhibiting data producers, data stewards, and data brokers in achieving FAIR goals for sharing biomedical data.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/data4020054 fatcat:qnx7ahj2yvbc5ccuu66asiko54

Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review

Kory Kreimeyer, Matthew Foster, Abhishek Pandey, Nina Arya, Gwendolyn Halford, Sandra F Jones, Richard Forshee, Mark Walderhaug, Taxiarchis Botsis
2017 Journal of Biomedical Informatics  
Seven literature databases were searched with a query combining the concepts of natural language processing and structured data capture.  ...  The NLP systems address a wide variety of important clinical and research tasks.  ...  Acknowledgements The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Food and Drug Administration or the Centers for Disease  ... 
doi:10.1016/j.jbi.2017.07.012 pmid:28729030 pmcid:PMC6864736 fatcat:puqdn2rxrngdhdejmbweabmrb4

Chapter 13: Mining Electronic Health Records in the Genomics Era

Joshua C. Denny, Fran Lewitter, Maricel Kann
2012 PLoS Computational Biology  
The combination of improved genomic analysis methods, decreasing genotyping costs, and increasing computing resources has led to an explosion of clinical genomic knowledge in the last decade.  ...  Combinations of structured and unstructured textual data can be mined to generate high-validity collections of cases and controls for a given condition.  ...  Some common NLP tasks needed in phenotype classification include identifying family medical history context and negated terms (e.g., ''no cardiac disease''), and removing drug allergies when searching  ... 
doi:10.1371/journal.pcbi.1002823 pmid:23300414 pmcid:PMC3531280 fatcat:ugktm6spyfe4tefawbwcgacrzu

Using Electronic Health Records To Generate Phenotypes For Research

Sarah A Pendergrass, Dana C Crawford
2018 Current Protocols in Human Genetics  
The near universal adoption of electronic health records nationally has the potential to provide population-scale real-world clinical data accessible for biomedical research, including genetic association  ...  We describe here common and emerging electronic phenotyping approaches applied to electronic health records, as well as current limitations of both the approaches and the biases associated with these clinically  ...  The linkage and leverage of patient and population data in EHRs can also be readily accessed for research purposes.  ... 
doi:10.1002/cphg.80 pmid:30516347 pmcid:PMC6318047 fatcat:zplma65p7ne2hjx2d45wper4gy

Portability of an algorithm to identify rheumatoid arthritis in electronic health records

Robert J Carroll, Will K Thompson, Anne E Eyler, Arthur M Mandelin, Tianxi Cai, Raquel M Zink, Jennifer A Pacheco, Chad S Boomershine, Thomas A Lasko, Hua Xu, Elizabeth W Karlson, Raul G Perez (+8 others)
2012 JAMIA Journal of the American Medical Informatics Association  
Retraining the model improved the average sensitivity at a specificity of 97% to 72% from the original 65%.  ...  Each institution compiled attributes from various sources in the EHR, including codified data and clinical narratives, which were searched using one of two natural language processing (NLP) systems.  ...  The Northwestern EDW was funded in part by a grant from the National Center for Research Resources, UL1RR025741.  ... 
doi:10.1136/amiajnl-2011-000583 pmid:22374935 pmcid:PMC3392871 fatcat:kg4he27nprckpfltmdzuwd3do4

Fine-grained information extraction from German transthoracic echocardiography reports

Martin Toepfer, Hamo Corovic, Georg Fette, Peter Klügl, Stefan Störk, Frank Puppe
2015 BMC Medical Informatics and Decision Making  
Extracted results populate a clinical data warehouse which supports clinical research.  ...  The final component has been mapped to the central elements of a standardized terminology, and it has been evaluated according to documents with different layouts.  ...  Typically, pipelines contain further processors to detect if concepts are negated, time dependent, or refer to family history, for instance, using regular expressions [22] .  ... 
doi:10.1186/s12911-015-0215-x pmid:26563260 pmcid:PMC4643516 fatcat:gl5vs2vjlrbktnq6lz6zqbcbn4

A new paradigm for accelerating clinical data science at Stanford Medicine [article]

Somalee Datta, Jose Posada, Garrick Olson, Wencheng Li, Ciaran O'Reilly, Deepa Balraj, Joseph Mesterhazy, Joseph Pallas, Priyamvada Desai, Nigam Shah
2020 arXiv   pre-print
Hospitals have a large amount of patient data and researchers have demonstrated the ability to reuse that data and AI approaches to derive novel insights, support patient care, and improve care quality  ...  The ecosystem is designed to bring the modern data science community to highly sensitive clinical data in a secure and collaborative big data analytics environment with a goal to enable bigger, better  ...  of 18 We thank Nigam Shah's lab for being early adopters of the dataset, and tools and providing us with feedback and support.  ... 
arXiv:2003.10534v1 fatcat:mbsbmigcrjhxtazfsqlrlvkmju

Secondary use of electronic health records for building cohort studies through top-down information extraction

Markus Kreuzthaler, Stefan Schulz, Andrea Berghold
2015 Journal of Biomedical Informatics  
Controlled clinical trials are usually supported with an in-front data aggregation system, which supports the storage of relevant information according to the trial context within a highly structured environment  ...  We analyze the obtained results in detail and highlight challenges and future directions for the secondary use of routine data in general.  ...  Acknowledgment This work was supported by the GEN-AU III grant (GATiB II, Workpackage 4) from the Austrian Ministry of Education, Science and Culture.  ... 
doi:10.1016/j.jbi.2014.10.010 pmid:25451102 fatcat:umft6ziagrezlaxxzpmahlnyem

Clinical Text Data in Machine Learning: Systematic Review

Irena Spasic, Goran Nenadic
2020 JMIR Medical Informatics  
Conclusions We identified the data annotation bottleneck as one of the key obstacles to machine learning approaches in clinical NLP.  ...  We identified 110 relevant studies and extracted information about text data used to support machine learning, NLP tasks supported, and their clinical applications.  ...  Acknowledgments The authors gratefully acknowledge the support from the Engineering and Physical Sciences Research Council for HealTex-UK Healthcare Text Analytics Research Network (Grant number EP/N027280  ... 
doi:10.2196/17984 pmid:32229465 fatcat:zbnsn4hi4zakhpukefktb72yo4

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records

Peggy L Peissig, Luke V Rasmussen, Richard L Berg, James G Linneman, Catherine A McCarty, Carol Waudby, Lin Chen, Joshua C Denny, Russell A Wilke, Jyotishman Pathak, David Carrell, Abel N Kho (+1 others)
2012 JAMIA Journal of the American Medical Informatics Association  
Objective There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data  ...  Discussion A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs.  ...  Fund award to the Northwest Institute of Genetic Medicine.  ... 
doi:10.1136/amiajnl-2011-000456 pmid:22319176 pmcid:PMC3277618 fatcat:32zmgcukxzbr3eql43k533jnxq

EMBnet.journal 18 Suppl. B

EMBnet Journal
2012 EMBnet journal  
This paper revises and extends the paper "ONCO-i2b2: improve patients selection through case-based information retrieval techniques", by D.  ...  National Research Council of Italy (CNR) and the Polish Academy of Sciences (PAN Acknowledgements This work is partial fulfillment of the research objective of "DM19410 -Laboratorio di Bioinformatica  ...  We are confident these tools will continue to facilitate important data management tasks in the context of massive amounts of data being generated in the biomedical domain.  ... 
doi:10.14806/ej.18.b.592 fatcat:wlwsmbdlfzbjtk7vyhiabdov6q

An Effective Approach to Biomedical Information Extraction with Limited Training Data [article]

Siddhartha Jonnalagadda
2011 arXiv   pre-print
Overall, the two main contributions of this work include the application of sentence simplification to association extraction as described above, and the use of distributional semantics for concept extraction  ...  This approach renders all the advantages offered in other semi-supervised machine learning systems, and, unlike other proposed semi-supervised approaches, it can be used on top of different basic frameworks  ...  Given the ability of distributional semantics to detect words appearing in similar context and to predict the appropriateness of a concept to a context, both these problems could be addressed automatically  ... 
arXiv:1107.5752v2 fatcat:n7rtfgpvarh7do2xar6opjec5q

Automatically tracking diabetes using information in physicians' notes

R.S. Bhatia, S McClinton, R.F. Davies
2011 Emerging Health Threats Jour  
Applying classification and anomaly detection techniques to real-world data W Edwards, A Vaid, and I Brooks 27.  ...  HAIISS Data Warehouse (HDW)-A new data access architecture for ESSENCE in the VA A Mostaghimi, G Oda, C Lucero, P Schirmer, J Lombardo, R Wojcik, and M Holodniy 54.  ...  Acknowledgements This work was supported in part by the International Development Research Centre of Canada (Award 105130) and National Science Foundation under grant number 0911032.  ... 
doi:10.3402/ehtj.v4i0.7176 pmid:24149041 pmcid:PMC3168227 fatcat:xawzrw5djfbj3cdkulmu4laawy
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