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Semantically Accessing Documents Using Conceptual Model Descriptions [chapter]

Terje Brasethvik, Jon Atle Gulla
1999 Lecture Notes in Computer Science  
This paper presents an approach to semantic document classification and retrieval based on Natural Language Processing and Conceptual Modeling.  ...  These are parsed using a DCG-like grammar, mapped into a Referent Model fragment and stored along with the document in RDF-XML syntax.  ...  All relevant information regarding patients and their treatment is recorded in a (medical) patient-journal.  ... 
doi:10.1007/3-540-48054-4_26 fatcat:q6qkcq5ly5dvtcmxpckf7zklty

Visualizing Semantic Structure of a Clinical Text Document

Jonah Kenei, Elisha Opiyo, Robert Oboko
2020 European Journal of Electrical Engineering and Computer Science  
These notes are useful as they provide comprehensive information about patients' health histories with many practical uses.  ...  A user evaluation demonstrates that the proposed method for visualizing and navigating a document's semantic structure facilitates a user's document information exploration.  ...  We are also thankful to MT samples for providing sample medical reports for this study.  ... 
doi:10.24018/ejece.2020.4.6.256 fatcat:zqogu4pxdjfztdwwbip4m735jq

Integration of Low Level Linguistic Information for Clinical Document Semantic Tagging

Hyeju Jang, Yun Jin, Sung Myaeng
2006 2006 IEEE International Conference on Information Reuse & Integration  
The semantic tagging, based on Hidden Markov Model (HMM), is performed on the text that has been tagged with Unified Medical Language System (UMLS), Part-of-Speech (POS), and abbreviation tags.  ...  In short, the semantic tagger gives more meaningful and abstract information by integrating different kinds of low-level information.  ...  records new knowledge without direct experiences.  ... 
doi:10.1109/iri.2006.252428 dblp:conf/iri/JangJM06 fatcat:gtu7ur6u6zhxhj6ikhdhbv4vay

SemTree: An index for supporting semantic retrieval of documents

Flora Amato, Aniello De Santo, Francesco Gargiulo, Vincenzo Moscato, Fabio Persia, Antonio Picariello, Silvestro Roberto Poccia
2015 2015 31st IEEE International Conference on Data Engineering Workshops  
In this paper, we propose SemTree, a novel semantic index for supporting retrieval of information from huge amount of document collections, assuming that semantics of a document can be effectively expressed  ...  by a set of (subject, predicate, object) statements as in the RDF model.  ...  This process requires from one hand a model for representing semantics attached to any kind of document (e.g. web pages, medical records, logs and more in general each type of textual documents), and from  ... 
doi:10.1109/icdew.2015.7129546 dblp:conf/icde/AmatoSGMPPP15 fatcat:pt6gxceglfhuxnbjmrfaup4osu

Exploiting Cognitive Computing and Frame Semantic Features for Biomedical Document Clustering

Danilo Dessì, Diego Reforgiato Recupero, Gianni Fenu, Sergio Consoli
2017 Extended Semantic Web Conference  
In this work we show how it is possible to cluster medical reports, based on features detected by using two emerging tools, IBM Watson and Framester, from a collection of text documents.  ...  Experiments and results have proved the quality of the resulting clusterings and the key role that these services can play.  ...  Section 2 includes past works related to clustering medical documents and improvements of data mining techniques with the employment of semantics.  ... 
dblp:conf/esws/DessiRFC17 fatcat:zwmqsg7k4jajlgetnpgbkmp6si

Evaluation of Co-occurring Terms in Clinical Documents Using Latent Semantic Indexing

Choonghyun Han, Sooyoung Yoo, Jinwook Choi
2011 Healthcare Informatics Research  
Clinical documents which can be characterized with co-occurring medical terms, various expressions for the same concepts, abbreviations, and typographical errors showed increased improvement with regards  ...  In addition, correlation between the co-occurrence of terms and similarities realized in this study is an important positive feature associated with LSI.  ...  As we expected there would be lots of co-occurring jargons in medical field compared with other fields, we performed an experiment showing the effect of term co-occurrence on document similarity.  ... 
doi:10.4258/hir.2011.17.1.24 pmid:21818454 pmcid:PMC3092990 fatcat:a573qvayv5cdfjl46cispx7wp4

Personalized Semantic Retrieval and Summarization of Web Based Documents

Salah T., Khaled M., Naveed Arshad
2013 International Journal of Advanced Computer Science and Applications  
In a proposed system, the Web documents are represented in concept vector model using WordNet. Personalization is used in a proposed system by building user model (UM).  ...  The results of the experiment shows that the proposed system, which is based on Semantic Web technology, can improve the accuracy and effectiveness for retrieving relevant Web documents.  ...  Persival [33] re-ranked the search results of queries for medical articles profiles keywords, associated concepts, and weights generated from an electronic patient record.  ... 
doi:10.14569/ijacsa.2013.040128 fatcat:7x7755lp45ddbf4onqdldlngfu

Semantic Inference on Clinical Documents: Combining Machine Learning Algorithms With an Inference Engine for Effective Clinical Diagnosis and Treatment

Shuo Yang, Ran Wei, Jingzhi Guo, Lida Xu
2017 IEEE Access  
Semantic inference on clinical documents: Combining machine learning algorithms with an inference engine for effective clinical diagnosis and treatment.  ...  INDEX TERMS Big data, case-based reasoning, clinical diagnosis, decision tree, data stream mining, disease detection, electronic health record, medical record, semantic integration.  ...  CLINICAL TABULAR DOCUMENT MODEL Each patient medical record corresponds to a medical examination on a given date [33] .  ... 
doi:10.1109/access.2017.2672975 fatcat:e7eu7xgx5vamxofjxlkwauqgu4

State of the art document clustering algorithms based on semantic similarity

Karwan Jacksi, Niyaz Salih
2020 Jurnal Informatika  
Salih and Jacksi (State of the art document clustering algorithms based on semantic similarity)  ...  It may help collect patients or records more effectively to assess the quality of the imaging diagnosis [40] .  ...  The important component is to present an overall structure for semantic text clustering based on data modeling from RDF.  ... 
doi:10.26555/jifo.v14i2.a17513 fatcat:g7wvf4xxzvczthl5qut2al72dm


2008 International Journal of Semantic Computing (IJSC)  
We describe a preliminary computational model of document explanation by an embodied conversational agent, in which appropriate form and location of hand gestures are used by the agent in explaining a  ...  Results from a pilot evaluation study indicate that individuals with low levels of domain knowledge prefer receiving explanations from such an agent rather than from a human.  ...  Thanks to Francisco Crespo and Thomas Brown for their assistance in conducting the evaluation study, to Mary Goodwin for being our expert in the second empirical study, and to our collaborators at Boston Medical  ... 
doi:10.1142/s1793351x08000348 fatcat:l4qg56figvcinlbpobwboyzcai

Implicit Entity Recognition in Clinical Documents

Sujan Perera, Pablo Mendes, Amit Sheth, Krishnaprasad Thirunarayan, Adarsh Alex, Christopher Heid, Greg Mott
2015 Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics  
With the increasing automation of health care information processing, it has become crucial to extract meaningful information from textual notes in electronic medical records.  ...  semantic similarity between sentences and entity models.  ...  Acknowledgement We acknowledge the medical students Logan Markins, Kara Joseph, and Robert Beaulieu of Wright State University for their assistance in creating the gold-standard corpus.  ... 
doi:10.18653/v1/s15-1028 dblp:conf/starsem/PereraMSTAHM15 fatcat:h54xjsnj2bd7he6hlrqov35sda

Disease causality extraction based on lexical semantics and document-clause frequency from biomedical literature

Dong-gi Lee, Hyunjung Shin
2017 BMC Medical Informatics and Decision Making  
The resulting network was compared with that of a previous study.  ...  In most disease networks, however, the relationship between diseases has been simply represented as an association.  ...  Acknowledgments The authors would like to gratefully acknowledge support from the National Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and  ... 
doi:10.1186/s12911-017-0448-y pmid:28539124 pmcid:PMC5444051 fatcat:ddj5we6bgjfhlkgskzrkgvxl4a

Visualizing search results and document collections using topic maps

David Newman, Timothy Baldwin, Lawrence Cavedon, Eric Huang, Sarvnaz Karimi, David Martinez, Falk Scholer, Justin Zobel
2010 Journal of Web Semantics  
Our topic maps are based on a topic model of the document collection, where the topic model is used to determine the semantic content of each document.  ...  This paper explores visualizations of document collections, which we call topic maps.  ...  We thank GEM for helping us understand the query process used in systematic reviews, and for supplying us with sample queries.  ... 
doi:10.1016/j.websem.2010.03.005 fatcat:mk5cjnogxrdhlbeiy37h2ulgxe

Assisting nurses in care documentation: from automated sentence classification to coherent document structures with subject headings

Hans Moen, Kai Hakala, Laura-Maria Peltonen, Hanna-Maria Matinolli, Henry Suhonen, Kirsi Terho, Riitta Danielsson-Ojala, Maija Valta, Filip Ginter, Tapio Salakoski, Sanna Salanterä
2020 Journal of Biomedical Semantics  
We describe the evaluation of a system aimed at assisting nurses in documenting patient care and potentially reducing the documentation workload.  ...  For classification the system relies on a neural network-based text classification model. The nursing notes are initially classified on sentence level.  ...  In an attempt to reduce the number of paragraphs created, to more closely simulate how nurses document, we have implemented an experimental post-processing step that enables the system to merge paragraphs  ... 
doi:10.1186/s13326-020-00229-7 pmid:32873340 fatcat:wot3jaevwnhjfpeoabkh6im7kq

Semantic concept-enriched dependence model for medical information retrieval

Sungbin Choi, Jinwook Choi, Sooyoung Yoo, Heechun Kim, Youngho Lee
2014 Journal of Biomedical Informatics  
Measurements: We performed leave-one-out cross validations on both a clinical document corpus (TREC Medical records track) and a medical literature corpus (OHSUMED), which are representative test collections  ...  These semantic concept-based dependence features were incorporated into a semantic concept-enriched dependence model (SCDM).  ...  Second, we conduct extensive experiments on both a clinical document corpus (TREC Medical records track) and a medical literature corpus (OH-SUMED).  ... 
doi:10.1016/j.jbi.2013.08.013 pmid:24036003 fatcat:e2dll5bvjbbazkcggar64zwhdu
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