Filters








1,774 Hits in 9.8 sec

Do You Need Embeddings Trained on a Massive Specialized Corpus for Your Clinical Natural Language Processing Task?

Antoine Neuraz, Vincent Looten, Bastien Rance, Nicolas Daniel, Nicolas Garcelon, Leonardo Campillos Llanos, Anita Burgun, Sophie Rosset
2019 Studies in Health Technology and Informatics  
We explore the impact of data source on word representations for different NLP tasks in the clinical domain in French (natural language understanding and text classification).  ...  We compared word embeddings (Fasttext) and language models (ELMo), learned either on the general domain (Wikipedia) or on specialized data (electronic health records, EHR).  ...  Tasks Natural language understanding in a virtual assistant (VA task) This task aims to provide natural language understanding (NLU) in a virtual assistant for clinicians to explore biological tests results  ... 
doi:10.3233/shti190533 pmid:31438230 fatcat:cij3nsah2remrk5r7gbuayrovu

Rethinking Search: Making Experts out of Dilettantes [article]

Donald Metzler, Yi Tay, Dara Bahri, Marc Najork
2021 arXiv   pre-print
Large pre-trained language models, by contrast, are capable of directly generating prose that may be responsive to an information need, but at present they are dilettantes rather than experts - they do  ...  Successful question answering systems offer a limited corpus created on-demand by human experts, which is neither timely nor scalable.  ...  Common natural language tasks, like masked contained in the corpus?  ... 
arXiv:2105.02274v1 fatcat:qdghlnv2nnfhnoo6eafdaxqxzy

Novel Event Detection and Classification for Historical Texts

Rachele Sprugnoli, Sara Tonelli
2019 Computational Linguistics  
can lead to the development of methodologies and tools that can assist historians in enhancing their work, while having an impact also on the field of Natural Language Processing.  ...  To this end, we release new annotation guidelines, a corpus, and new models for automatic annotation.  ...  Acknowledgments The authors would like to thank Giovanni Moretti for technical assistance, Anna Feltracco for her help with inter-annotator agreement, and the anonymous reviewers for their helpful comments  ... 
doi:10.1162/coli_a_00347 fatcat:bp3pv7f27fetrfq2cuzyc5lany

DATLMedQA: A Data Augmentation and Transfer Learning Based Solution for Medical Question Answering

Shuohua Zhou, Yanping Zhang
2021 Applied Sciences  
In response to this demand, medical question answering and question generation tasks have become an important part of natural language processing (NLP).  ...  In this research, we propose a BERT medical pretraining model, using GPT-2 for question augmentation and T5-Small for topic extraction, calculating the cosine similarity of the extracted topic and using  ...  Data Availability Statement: The data and code supporting the conclusions of this article are available at https://github.com/ShuohuaZhou-NLPer/Question_Answering/, accessed on 17 November 2021.  ... 
doi:10.3390/app112311251 fatcat:mxnpggeymvg4ze2nygk675ud3u

Natural language generation for electronic health records

Scott H. Lee
2018 npj Digital Medicine  
After being trained end-to-end on authentic records, the model can generate realistic chief complaint text that preserves much of the epidemiological information in the original data.  ...  A variety of methods existing for generating synthetic electronic health records (EHRs), but they are not capable of generating unstructured text, like emergency department (ED) chief complaints, history  ...  The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.  ... 
doi:10.1038/s41746-018-0070-0 fatcat:sirstvhjrfexppaks4s2mv5bou

Natural language generation for electronic health records

Scott H Lee
2018 npj Digital Medicine  
This is an important advance that we hope will facilitate the development of machine-learning methods for clinical decision support, disease surveillance, and other data-hungry applications in biomedical  ...  After being trained end-to-end on authentic records, the model can generate realistic chief complaint text that appears to preserve the epidemiological information encoded in the original record-sentence  ...  The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.  ... 
pmid:30687797 pmcid:PMC6345174 fatcat:u32ip5qibbcz3oucwbimqogk2m

Word2Vec inversion and traditional text classifiers for phenotyping lupus

Clayton A. Turner, Alexander D. Jacobs, Cassios K. Marques, James C. Oates, Diane L. Kamen, Paul E. Anderson, Jihad S. Obeid
2017 BMC Medical Informatics and Decision Making  
This task can be automated using text classifiers based on Natural Language Processing (NLP) techniques along with pattern recognition machine learning (ML) algorithms.  ...  Identifying patients with certain clinical criteria based on manual chart review of doctors' notes is a daunting task given the massive amounts of text notes in the electronic health records (EHR).  ...  Acknowledgements We would like to acknowledge Adrian Michael Nida for his early work on this project during his graduate training at MUSC.  ... 
doi:10.1186/s12911-017-0518-1 pmid:28830409 pmcid:PMC5568290 fatcat:ptcp4xs37bbydnpjcyodltb7s4

Predicting Semantic Similarity Between Clinical Sentence Pairs Using Transformer Models: Evaluation and Representational Analysis

Mark Ormerod, Jesús Martínez del Rincón, Barry Devereux
2021 JMIR Medical Informatics  
Language Processing for Clinical Data.  ...  Semantic textual similarity (STS) is a natural language processing (NLP) task that involves assigning a similarity score to 2 snippets of text based on their meaning.  ...  Acknowledgments This research was funded by a Northern Ireland Health and Social Care Board eHealth Directorate grant (grant no. 24F-1801) to BD. Conflicts of Interest None declared.  ... 
doi:10.2196/23099 pmid:34037527 fatcat:s2gbcy5x7za4bexet2376lve4q

Deep Text Mining of Instagram Data without Strong Supervision

Kim Hammar, Shatha Jaradat, Nima Dokoohaki, Mihhail Matskin
2018 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)  
With our experiments, we confirm that word embeddings are a useful asset for information extraction.  ...  In this context, we analyze a corpora of Instagram posts from the fashion domain, introduce a system for extracting fashion attributes from Instagram, and train a deep clothing classifier with weak supervision  ...  NATURAL LANGUAGE PROCESSING can be formulated as an information extraction task.  ... 
doi:10.1109/wi.2018.00-94 dblp:conf/webi/HammarJDM18 fatcat:2x3qskb7njhcfhqf6rqcd7ti6y

Neural Machine Reading Comprehension: Methods and Trends

Shanshan Liu, Xin Zhang, Sheng Zhang, Hui Wang, Weiming Zhang
2019 Applied Sciences  
Although research on MRC based on deep learning is flourishing, there remains a lack of a comprehensive survey summarizing existing approaches and recent trends, which motivated the work presented in this  ...  Machine reading comprehension (MRC), which requires a machine to answer questions based on a given context, has attracted increasing attention with the incorporation of various deep-learning techniques  ...  Answer: ent193 Multiple Choice RACE [10] Context: If you have a cold or flu, you must always deal with used tissues carefully. Do not leave dirty tissues on your desk or on the floor.  ... 
doi:10.3390/app9183698 fatcat:bpwwfikrpvh4dhphyl3ezpnn5e

Rapid Development of Competitive Translation Engines for Access to Multilingual COVID-19 Information

Andy Way, Rejwanul Haque, Guodong Xie, Federico Gaspari, Maja Popović, Alberto Poncelas
2020 Informatics  
Our MT systems trained on COVID-19 data are freely available for anyone to use to help translate information (such as promoting good practice for symptom identification, prevention, and treatment) published  ...  In cases where language is a barrier to access of pertinent information, machine translation (MT) may help people assimilate information published in different languages.  ...  Acknowledgments: Many thanks to the five anonymous reviewers for their helpful suggestions as to how to improve this paper. Any remaining errors are of course our own fault.  ... 
doi:10.3390/informatics7020019 fatcat:pkreiqxzqbehlpqpwpc27lgno4

First-principle study on honeycomb fluorated-InTe monolayer with large Rashba spin splitting and direct bandgap

Kaixuan Li, Xiujuan Xian, Jiafu Wang, Niannian Yu
2019 Applied Surface Science  
Although research on MRC based on deep learning is flourishing, there remains a lack of a comprehensive survey summarizing existing approaches and recent trends, which motivated the work presented in this  ...  Machine reading comprehension (MRC), which requires a machine to answer questions based on a given context, has attracted increasing attention with the incorporation of various deep-learning techniques  ...  Conclusion This article presents a comprehensive survey on the progresses of neural machine reading comprehension.  ... 
doi:10.1016/j.apsusc.2018.11.214 fatcat:dg2eusl7ufhttcsqlllyiisxb4

From Theories on Styles to their Transfer in Text: Bridging the Gap with a Hierarchical Survey [article]

Enrica Troiano and Aswathy Velutharambath and Roman Klinger
2021 arXiv   pre-print
As a natural language generation task, style transfer aims at re-writing existing texts, and specifically, it creates paraphrases that exhibit some desired stylistic attributes.  ...  A handful of surveys give a methodological overview of the field, but they do not support researchers to focus on specific styles.  ...  To solve this problem, the authors moved to language models as a different type of discriminator which overcomes the need for adversarial training: a language model trained on the target sentiment data  ... 
arXiv:2110.15871v2 fatcat:ddpowdm6pbazzd5mwl65nrge5q

Enriching the University ELT Curriculum with Insights from ELF

Franca Poppi
2016 LCM - La Collana / The Series  
Le riproduzioni effettuate per finalità di carattere professionale, economico o commerciale o comunque per uso diverso da quello personale possono essere effettuate a seguito di specifica autorizzazione  ...  Translation Studies) -Hugo de Burgh (Chinese Media Studies) Kristen Brustad (Arabic Linguistics) -Daniel Coste (French Language) Luciano Curreli (Italian Literature) -Denis Ferraris (Italian Literature  ...  How do you feel about this development? How does it affect you? Please give your opinion on the following statements.  ... 
doi:10.7359/791-2016-popp fatcat:trj3vywsmvc65djpe5dr5tzhga

Outpatient Text Classification Using Attention-Based Bidirectional LSTM for Robot-Assisted Servicing in Hospital

Che-Wen Chen, Shih-Pang Tseng, Ta-Wen Kuan, Jhing-Fa Wang
2020 Information  
Through natural language processing (NLP), the information in the dialog text was extracted, sorted, and converted to train the long-short term memory (LSTM) deep learning model.  ...  In general, patients who are unwell do not know with which outpatient department they should register, and can only get advice after they are diagnosed by a family doctor.  ...  Which department do I need to check for these symptoms? Thank you. QA Text content Question Hi! Doctor, I have occasionally been dizzy recently, and canAnswer Hello!  ... 
doi:10.3390/info11020106 fatcat:usrga42frjg67o3q73vjfn5ncq
« Previous Showing results 1 — 15 out of 1,774 results