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Clinical Natural Language Processing in 2015: Leveraging the Variety of Texts of Clinical Interest

A. Névéol, P. Zweigenbaum
2016 IMIA Yearbook of Medical Informatics  
Foundational progress in the field makes it possible to leverage a larger variety of texts of clinical interest for healthcare purposes.  ...  Objective: To summarize recent research and present a selection of the best papers published in 2015 in the field of clinical Natural Language Processing (NLP).  ...  [26] use psychiatric and general internal medicine discharge summaries to assign polarity scores for a positive/negative sentiment.  ... 
doi:10.15265/iy-2016-049 pmid:27830256 pmcid:PMC5171575 fatcat:lpjlk27gxzc7jd3gindlth2wcm

Neural Natural Language Processing for Unstructured Data in Electronic Health Records: a Review [article]

Irene Li, Jessica Pan, Jeremy Goldwasser, Neha Verma, Wai Pan Wong, Muhammed Yavuz Nuzumlalı, Benjamin Rosand, Yixin Li, Matthew Zhang, David Chang, R. Andrew Taylor, Harlan M. Krumholz (+1 others)
2021 arXiv   pre-print
Electronic health records (EHRs), digital collections of patient healthcare events and observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and research.  ...  Recently, however, newer neural network and deep learning approaches to Natural Language Processing (NLP) have made considerable advances, outperforming traditional statistical and rule-based systems on  ...  Several papers have used CNNs to model relation extraction. Sahu et al. [195] used a standard CNN augmented with word-level features to extract relations from clinical discharge summaries.  ... 
arXiv:2107.02975v1 fatcat:nayhw7gadfdzrovycdkvzy75pi

Pre-trained Language Models in Biomedical Domain: A Systematic Survey [article]

Benyou Wang, Qianqian Xie, Jiahuan Pei, Prayag Tiwari, Zhao Li, Jie fu
2021 arXiv   pre-print
Pre-trained language models (PLMs) have been the de facto paradigm for most natural language processing (NLP) tasks.  ...  health records, protein, and DNA sequences for various biomedical tasks.  ...  Event Extraction. Event extraction is another important task for mining structured knowledge from biomedical data.  ... 
arXiv:2110.05006v2 fatcat:aykwfhgi4jgmfovissgdvknny4

An Examination of the Statistical Laws of Semantic Change in Clinical Notes

Kevin J Peterson, Hongfang Liu
2021 AMIA Annual Symposium Proceedings  
In this study, we examine two previously described semantic change laws based on word frequency and polysemy, and analyze how they apply to the clinical domain.  ...  Using a corpus spanning eighteen years of clinical notes, we find that the previously described laws of semantic change hold for our data set.  ...  Our clinical notes corpus was quite heterogeneous in regards to note type composition and included over one hundred different categories of notes, including progress notes, evaluations, discharge summaries  ... 
pmid:34457167 pmcid:PMC8378619 fatcat:zhsmwfw4ynfgpio6zgouotmdhi

Natural Language Processing for Information Extraction [article]

Sonit Singh
2018 arXiv   pre-print
This explosion of information and need for more sophisticated and efficient information handling tools gives rise to Information Extraction(IE) and Information Retrieval(IR) technology.  ...  Information Extraction systems takes natural language text as input and produces structured information specified by certain criteria, that is relevant to a particular application.  ...  Several methods have been proposed to extract events from text. Early approaches include Pattern-matching which try to use context information for finding relations between entities.  ... 
arXiv:1807.02383v1 fatcat:3bdyidbjp5hn7c2w4iqve4ajvi

DeepHealth: Review and challenges of artificial intelligence in health informatics [article]

Gloria Hyunjung Kwak, Pan Hui
2020 arXiv   pre-print
online communication health, as well as challenges and promising directions for future research.  ...  The demand for it in health informatics is also increasing, and we can expect to see the potential benefits of its applications in healthcare.  ...  Reference [233] extracted clinical concepts from free clinical narratives with relevant external resources (Wikipedia, Mayo Clinic), and trained Deep Q-Network (DQN) with two states (current clinical  ... 
arXiv:1909.00384v2 fatcat:sy7pm2c2uvdd3pal2russn4xri

Program Committee

2006 2006 Sixth IEEE International Workshop on Source Code Analysis and Manipulation  
Support for students came from the Global Wordnet Association. We would like to thank the programme committee for their thoughtful and timely reviews. The conference homepage is  ...  Coaching in Computer Assisted Language Learning using Machine Translation Technology.  ...  Several others contributing to its content are: Polish language version of Wikipedia and Wikisource, Walenty valency dictionary (Przepiórkowski et al., 2014) and National Corpus of Polish (Przepiórkowski  ... 
doi:10.1109/scam.2006.23 dblp:conf/scam/X06c fatcat:2dhsf7loj5hlffu2jxpmlo2qcq

Automatic negation detection in narrative pathology reports

Ying Ou, Jon Patrick
2015 Artificial Intelligence in Medicine  
A relation extraction system was presented to extract four relations from the lymphoma corpus.  ...  The goal of this thesis is to extract pertinent information from free-text pathology reports and automatically populate structured reports for three cancer diseases, namely melanoma, colorectal cancer,  ...  To extract concepts from clinical documents, Torii et al replaced one of its components -BioThesaurus with a collection of clinical terms extracted from discharge summaries, supplemented the section header  ... 
doi:10.1016/j.artmed.2015.03.001 pmid:25990897 fatcat:yrijkncnsvht7lonmaqt7uyya4

Beyond Social Media Analytics: Understanding Human Behaviour and Deep Emotion using Self Structuring Incremental Machine Learning [article]

Tharindu Bandaragoda
2020 arXiv   pre-print
partners) against time, demographics and clinical factors.  ...  Secondly for the slow-paced social data, a suite of new machine learning and natural language processing techniques were developed to automatically capture self-disclosed information of the individuals  ...  Existing work on clinical event extraction is mostly developed for the clinical narratives in Electronic Health Records (EHR) and discharge summaries.  ... 
arXiv:2009.09078v1 fatcat:izo3eyjc4vdo3jnttt7omvsv5q

Anaphoric reference in clinical reports: Characteristics of an annotated corpus

Wendy W. Chapman, Guergana K. Savova, Jiaping Zheng, Melissa Tharp, Rebecca Crowley
2012 Journal of Biomedical Informatics  
We annotated a set of 180 clinical reports (surgical pathology, radiology, discharge summaries, and emergency department) from two institutions to indicate all anaphor-antecedent pairs.  ...  Understanding how anaphoric reference is exhibited in clinical reports is critical to developing reference resolution algorithms and to identifying peculiarities of clinical text that may alter the features  ...  The ODIE toolkitsoftware for information extraction and ontology development.  ... 
doi:10.1016/j.jbi.2012.01.010 pmid:22343015 fatcat:6tppus7qfvcdtoivkm45xxv23u

Open challenges for data stream mining research

Georg Krempl, Myra Spiliopoulou, Jerzy Stefanowski, Indre Žliobaite, Dariusz Brzeziński, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi
2014 SIGKDD Explorations  
Another body of literature focuses on developing languages for querying Tweets.  ...  Another body of literature focuses on developing languages for querying Tweets.  ...  Acknowledgments We would like to thank the participants of the RealStream2013 workshop at ECMLPKDD2013 in Prague, and in particular Bernhard Pfahringer and George Forman, for suggestions and discussions  ... 
doi:10.1145/2674026.2674028 fatcat:y3bozzeohveibgxb5wmiwfcogm

Leveraging Data Science to Combat COVID-19: A Comprehensive Review

Siddique Latif, Muhammad Usman, Sanaullah Manzoor, Waleed Iqbal, Junaid Qadir, Gareth Tyson, Ignacio Castro, Adeel Razi, Maged N. Kamel Boulos, Adrian Weller, Jon Crowcroft
2020 IEEE Transactions on Artificial Intelligence  
Information extraction from clinical studies is already being performed [41] using language processing models such as [42] .  ...  Ophir et al. extract visual features from volumetric chest CT exams for the detection of COVID-19.  ...  He leans toward a "build and learn" paradigm for research. From 2016 to 2018, he was the Programm Chair at the Turing, the U.K.'  ... 
doi:10.1109/tai.2020.3020521 fatcat:34u4p5ss6ngpxg6us3ht6a4dla

Bio-SCoRes: A Smorgasbord Architecture for Coreference Resolution in Biomedical Text

Halil Kilicoglu, Dina Demner-Fushman, Tudor Groza
2016 PLoS ONE  
In addition, we evaluated our approach on two other corpora (i2b2/VA discharge summaries and protein coreference dataset) to investigate its generality and ease of adaptation to other biomedical text types  ...  Resolving coreference successfully can have a significant positive effect on downstream natural language processing tasks, such as information extraction and question answering.  ...  Acknowledgments We thank Sonya Shooshan and Laritza Rodriguez for their contributions to the annotation study. This work was supported by the intramural research program at the U.S.  ... 
doi:10.1371/journal.pone.0148538 pmid:26934708 pmcid:PMC4774913 fatcat:eqtpgxqjivg2rgn4oqbpbiiqqq

Computational Socioeconomics [article]

Jian Gao, Yi-Cheng Zhang, Tao Zhou
2019 arXiv   pre-print
individual socioeconomic status and demographic, and the real-time monitoring of emergent events.  ...  Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development.  ...  [799] determined the degree of building damage based on the texture features extracted from pre-and post-event VHR satellite imagery.  ... 
arXiv:1905.06166v1 fatcat:kvhy2hpzgvg2vnqhdjfyjfidqi

Deep Learning applications for COVID-19

Connor Shorten, Taghi M. Khoshgoftaar, Borko Furht
2021 Journal of Big Data  
Natural Language Processing applications include mining COVID-19 research for Information Retrieval and Question Answering, as well as Misinformation Detection, and Public Sentiment Analysis.  ...  These limitations include Interpretability, Generalization Metrics, Learning from Limited Labeled Data, and Data Privacy.  ...  Opinions, findings, conclusions, or recommendations in this paper are the authors' and do not reflect the views of the NSF.  ... 
doi:10.1186/s40537-020-00392-9 pmid:33457181 pmcid:PMC7797891 fatcat:aokxo63z2rhdpfxo3egyf3xpcm
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