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363 result(s) for 'natural language processing' within BMC Medical Informatics and Decision Making

Page 3 of 8

  1. Family history information (FHI) described in unstructured electronic health records (EHRs) is a valuable information source for patient care and scientific researches. Since FHI is usually described in the fo...

    Authors: Hong-Jie Dai

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 10):257

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 19 Supplement 10

  2. Receiving extraneous articles in response to a query submitted to MEDLINE/PubMed is common. When submitting a multi-word query (which is the majority of queries submitted), the presence of all query words with...

    Authors: Mir S Siadaty, Jianfen Shu and William A Knaus

    Citation: BMC Medical Informatics and Decision Making 2007 7:1

    Content type: Software

    Published on:

  3. This paper proposes the use of decision trees as the basis for automatically extracting information from published randomized controlled trial (RCT) reports. An exploratory analysis of RCT abstracts is underta...

    Authors: Grace Y Chung and Enrico Coiera

    Citation: BMC Medical Informatics and Decision Making 2008 8:48

    Content type: Research article

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  4. Drug label, or packaging insert play a significant role in all the operations from production through drug distribution channels to the end consumer. Image of the label also called Display Panel or label could...

    Authors: Xiangwen Liu, Joe Meehan, Weida Tong, Leihong Wu, Xiaowei Xu and Joshua Xu

    Citation: BMC Medical Informatics and Decision Making 2020 20:68

    Content type: Research article

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  5. The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving inter...

    Authors: Erik Sundvall, Rahil Qamar, Mikael Nyström, Mattias Forss, Håkan Petersson, Daniel Karlsson, Hans Åhlfeldt and Alan Rector

    Citation: BMC Medical Informatics and Decision Making 2008 8(Suppl 1):S7

    Content type: Proceedings

    Published on:

    This article is part of a Supplement: Volume 8 Supplement 1

  6. Clinical trials are one of the most important sources of evidence for guiding evidence-based practice and the design of new trials. However, most of this information is available only in free text - e.g., in j...

    Authors: Svetlana Kiritchenko, Berry de Bruijn, Simona Carini, Joel Martin and Ida Sim

    Citation: BMC Medical Informatics and Decision Making 2010 10:56

    Content type: Technical advance

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  7. Text-based patient medical records are a vital resource in medical research. In order to preserve patient confidentiality, however, the U.S. Health Insurance Portability and Accountability Act (HIPAA) requires...

    Authors: Ishna Neamatullah, Margaret M Douglass, Li-wei H Lehman, Andrew Reisner, Mauricio Villarroel, William J Long, Peter Szolovits, George B Moody, Roger G Mark and Gari D Clifford

    Citation: BMC Medical Informatics and Decision Making 2008 8:32

    Content type: Research article

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  8. Extraction of clinical information such as medications or problems from clinical text is an important task of clinical natural language processing (NLP). Rule-based methods are often...

    Authors: Son Doan, Nigel Collier, Hua Xu, Pham Hoang Duy and Tu Minh Phuong

    Citation: BMC Medical Informatics and Decision Making 2012 12:36

    Content type: Research article

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  9. The Named Entity Recognition (NER) task as a key step in the extraction of health information, has encountered many challenges in Chinese Electronic Medical Records (EMRs). Firstly, the casual use of Chinese a...

    Authors: Xiaoling Cai, Shoubin Dong and Jinlong Hu

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):65

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  10. Systematized Nomenclature of Medicine—Clinical Terms (SNOMED CT, hereafter abbreviated SCT) is a comprehensive medical terminology used for standardizing the storage, retrieval, and exchange of electronic heal...

    Authors: Shaker El-Sappagh, Francesco Franda, Farman Ali and Kyung-Sup Kwak

    Citation: BMC Medical Informatics and Decision Making 2018 18:76

    Content type: Research article

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  11. Healthcare providers generate a huge amount of biomedical data stored in either legacy system (paper-based) format or electronic medical records (EMR) around the world, which are collectively referred to as bi...

    Authors: Ligang Luo, Liping Li, Jiajia Hu, Xiaozhe Wang, Boulin Hou, Tianze Zhang and Lue Ping Zhao

    Citation: BMC Medical Informatics and Decision Making 2016 16:114

    Content type: Technical advance

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  12. Making evidence-based decisions often requires comparison of two or more options. Research-based evidence may exist which quantifies how likely the outcomes are for each option. Understanding these numeric est...

    Authors: Lyndal J Trevena, Brian J Zikmund-Fisher, Adrian Edwards, Wolfgang Gaissmaier, Mirta Galesic, Paul KJ Han, John King, Margaret L Lawson, Suzanne K Linder, Isaac Lipkus, Elissa Ozanne, Ellen Peters, Danielle Timmermans and Steven Woloshin

    Citation: BMC Medical Informatics and Decision Making 2013 13(Suppl 2):S7

    Content type: Review

    Published on:

    This article is part of a Supplement: Volume 13 Supplement 2

  13. In this study, using sampled clinical documents associated with a cohort of patients who received their primary care at Mayo Clinic, we investigated the associations between problem list and practice setting thro...

    Authors: Liwei Wang, Yanshan Wang, Feichen Shen, Majid Rastegar-Mojarad and Hongfang Liu

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 3):69

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 19 Supplement 3

  14. MEDLINE is the most widely used medical bibliographic database in the world. Most of its citations are in English and this can be an obstacle for some researchers to access the information the database contain...

    Authors: Matthieu Schuers, Mher Joulakian, Gaetan Kerdelhué, Léa Segas, Julien Grosjean, Stéfan J. Darmoni and Nicolas Griffon

    Citation: BMC Medical Informatics and Decision Making 2017 17:94

    Content type: Research article

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  15. Manual eligibility screening (ES) for a clinical trial typically requires a labor-intensive review of patient records that utilizes many resources. Leveraging state-of-the-art natural language processing (NLP) an...

    Authors: Yizhao Ni, Jordan Wright, John Perentesis, Todd Lingren, Louise Deleger, Megan Kaiser, Isaac Kohane and Imre Solti

    Citation: BMC Medical Informatics and Decision Making 2015 15:28

    Content type: Research article

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  16. The necessity to translate eligibility criteria from free text into decision rules that are compatible with data from the electronic health record (EHR) constitutes the main challenge when developing and deplo...

    Authors: Felix Köpcke, Dorota Lubgan, Rainer Fietkau, Axel Scholler, Carla Nau, Michael Stürzl, Roland Croner, Hans-Ulrich Prokosch and Dennis Toddenroth

    Citation: BMC Medical Informatics and Decision Making 2013 13:134

    Content type: Research article

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  17. The rapid adoption of electronic health records (EHRs) holds great promise for advancing medicine through practice-based knowledge discovery. However, the validity of EHR-based clinical research is questionabl...

    Authors: Sunyang Fu, Lester Y. Leung, Anne-Olivia Raulli, David F. Kallmes, Kristin A. Kinsman, Kristoff B. Nelson, Michael S. Clark, Patrick H. Luetmer, Paul R. Kingsbury, David M. Kent and Hongfang Liu

    Citation: BMC Medical Informatics and Decision Making 2020 20:60

    Content type: Research article

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  18. In this study we implemented and developed state-of-the-art machine learning (ML) and natural language processing (NLP) technologies and built a computerized...

    Authors: Qi Li, Stephen Andrew Spooner, Megan Kaiser, Nataline Lingren, Jessica Robbins, Todd Lingren, Huaxiu Tang, Imre Solti and Yizhao Ni

    Citation: BMC Medical Informatics and Decision Making 2015 15:37

    Content type: Research article

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  19. Pharmacovigilance aims to uncover and understand harmful side-effects of drugs, termed adverse events (AEs). Although the current process of pharmacovigilance is very systematic, the increasing amount of infor...

    Authors: SriJyothsna Yeleswarapu, Aditya Rao, Thomas Joseph, Vangala Govindakrishnan Saipradeep and Rajgopal Srinivasan

    Citation: BMC Medical Informatics and Decision Making 2014 14:13

    Content type: Research article

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  20. The amount of patient-related information within clinical information systems accumulates over time, especially in cases where patients suffer from chronic diseases with many hospitalizations and consultations...

    Authors: Markus Kreuzthaler, Bastian Pfeifer, Jose Antonio Vera Ramos, Diether Kramer, Victor Grogger, Sylvia Bredenfeldt, Markus Pedevilla, Peter Krisper and Stefan Schulz

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 3):72

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 19 Supplement 3

  21. Narrative text is a useful way of identifying injury circumstances from the routine emergency department data collections. Automatically classifying narratives based on machine learning techniques is a promisi...

    Authors: Lin Chen, Kirsten Vallmuur and Richi Nayak

    Citation: BMC Medical Informatics and Decision Making 2015 15(Suppl 1):S5

    Content type: Research article

    Published on:

    This article is part of a Supplement: Volume 15 Supplement 1

  22. Family history (FH) information, including family members, side of family of family members (i.e., maternal or paternal), living status of family members, observations (diseases) of family members, etc., is very ...

    Authors: Xue Shi, Dehuan Jiang, Yuanhang Huang, Xiaolong Wang, Qingcai Chen, Jun Yan and Buzhou Tang

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 10):277

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 19 Supplement 10

  23. It has been shown that the entities in everyday clinical text are often expressed in a way that varies from how they are expressed in the nomenclature. Owing to lots of synonyms, abbreviations, medical jargons...

    Authors: Rui Zhang, Jialin Liu, Yong Huang, Miye Wang, Qingke Shi, Jun Chen and Zhi Zeng

    Citation: BMC Medical Informatics and Decision Making 2017 17:54

    Content type: Research article

    Published on:

  24. In this study, we focus on building a fine-grained entity annotation corpus with the corresponding annotation guideline of traditional Chinese medicine (TCM) clinical records. Our aim is to provide a basis for...

    Authors: Tingting Zhang, Yaqiang Wang, Xiaofeng Wang, Yafei Yang and Ying Ye

    Citation: BMC Medical Informatics and Decision Making 2020 20:64

    Content type: Research article

    Published on:

  25. Learning deep representations of clinical events based on their distributions in electronic health records has been shown to allow for subsequent training of higher-performing predictive models compared to the...

    Authors: Aron Henriksson, Jing Zhao, Hercules Dalianis and Henrik Boström

    Citation: BMC Medical Informatics and Decision Making 2016 16(Suppl 2):69

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 16 Supplement 2

  26. Chinese word segmentation (CWS) and part-of-speech (POS) tagging are two fundamental tasks of Chinese text processing. They are usually preliminary steps for lots of Chinese natural language processing (NLP) task...

    Authors: Ying Xiong, Zhongmin Wang, Dehuan Jiang, Xiaolong Wang, Qingcai Chen, Hua Xu, Jun Yan and Buzhou Tang

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 2):66

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 19 Supplement 2

  27. In this editorial, we first summarize the Third International Workshop on Semantics-Powered Data Analytics (SEPDA 2018) held on December 3, 2018 in conjunction with the 2018 IEEE International Conference on Bi...

    Authors: Zhe He, Jiang Bian, Cui Tao and Rui Zhang

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 4):148

    Content type: Introduction

    Published on:

    This article is part of a Supplement: Volume 19 Supplement 4

  28. Health question-answering (QA) systems have become a typical application scenario of Artificial Intelligent (AI). An annotated question corpus is prerequisite for training machines to understand health informa...

    Authors: Haihong Guo, Xu Na and Jiao Li

    Citation: BMC Medical Informatics and Decision Making 2018 18(Suppl 1):16

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 18 Supplement 1

  29. Health professionals and consumers use different terms to express medical events or concerns, which makes the communication barriers between the professionals and consumers. This may lead to bias in the diagno...

    Authors: Li Hou, Hongyu Kang, Yan Liu, Luqi Li and Jiao Li

    Citation: BMC Medical Informatics and Decision Making 2018 18(Suppl 5):120

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 18 Supplement 5

  30. Over a period of 40 years, SNOMED has developed from a pathology-specific nomenclature (SNOP) into a logic-based health care terminology. In spite of its long existence and continuous evolvement, it is yet unk...

    Authors: Ronald Cornet and Nicolette de Keizer

    Citation: BMC Medical Informatics and Decision Making 2008 8(Suppl 1):S2

    Content type: Proceedings

    Published on:

    This article is part of a Supplement: Volume 8 Supplement 1

  31. Relationships between bio-entities (genes, proteins, diseases, etc.) constitute a significant part of our knowledge. Most of this information is documented as unstructured text in different forms, such as book...

    Authors: Kaixian Yu, Pei-Yau Lung, Tingting Zhao, Peixiang Zhao, Yan-Yuan Tseng and Jinfeng Zhang

    Citation: BMC Medical Informatics and Decision Making 2018 18(Suppl 2):42

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 18 Supplement 2

  32. De-identification is a critical technology to facilitate the use of unstructured clinical text while protecting patient privacy and confidentiality. The clinical natural language processing (NLP) community has in...

    Authors: Xi Yang, Tianchen Lyu, Qian Li, Chih-Yin Lee, Jiang Bian, William R. Hogan and Yonghui Wu

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):232

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 19 Supplement 5

  33. Virtual Patients are a well-known and widely used form of interactive software used to simulate aspects of patient care that students are increasingly less likely to encounter during their studies. However, to...

    Authors: Marcus D Bloice, Klaus-Martin Simonic and Andreas Holzinger

    Citation: BMC Medical Informatics and Decision Making 2014 14:66

    Content type: Software

    Published on:

  34. Constrained budgets within healthcare systems and the need to efficiently allocate resources often necessitate the valuation of healthcare interventions and services. However, when a technological product is d...

    Authors: Emmanouil Mentzakis, Daria Tkacz and Carol Rivas

    Citation: BMC Medical Informatics and Decision Making 2020 20:95

    Content type: Research article

    Published on:

  35. Imaging examinations, such as ultrasonography, magnetic resonance imaging and computed tomography scans, play key roles in healthcare settings. To assess and improve the quality of imaging diagnosis, we need t...

    Authors: Tao Zheng, Yimei Gao, Fei Wang, Chenhao Fan, Xingzhi Fu, Mei Li, Ya Zhang, Shaodian Zhang and Handong Ma

    Citation: BMC Medical Informatics and Decision Making 2019 19:156

    Content type: Research article

    Published on:

  36. We extracted genetic testing information and patient medical records from EHR systems at Mayo Clinic. Clinical features have been semi-automatically annotated from the clinical notes by applying a Natural Language

    Authors: Qian Zhu, Hongfang Liu, Christopher G Chute and Matthew Ferber

    Citation: BMC Medical Informatics and Decision Making 2015 15(Suppl 4):S3

    Content type: Research article

    Published on:

    This article is part of a Supplement: Volume 15 Supplement 4

  37. The US Veterans Administration (VA) has developed a robust and mature computational infrastructure in support of its electronic health record (EHR). Web technology offers a powerful set of tools for structurin...

    Authors: Nallakkandi Rajeevan, Kristina M. Niehoff, Peter Charpentier, Forrest L. Levin, Amy Justice, Cynthia A. Brandt, Terri R. Fried and Perry L. Miller

    Citation: BMC Medical Informatics and Decision Making 2017 17:111

    Content type: Correspondence

    Published on:

  38. Record linkage refers to the process of joining records that relate to the same entity or event in one or more data collections. In the absence of a shared, unique key, record linkage involves the comparison o...

    Authors: Tim Churches, Peter Christen, Kim Lim and Justin Xi Zhu

    Citation: BMC Medical Informatics and Decision Making 2002 2:9

    Content type: Research article

    Published on:

  39. Diagnostic error is a significant problem in specialities characterised by diagnostic uncertainty such as primary care, emergency medicine and paediatrics. Despite wide-spread availability, computerised aids h...

    Authors: Padmanabhan Ramnarayan, Andrew Winrow, Michael Coren, Vasanta Nanduri, Roger Buchdahl, Benjamin Jacobs, Helen Fisher, Paul M Taylor, Jeremy C Wyatt and Joseph Britto

    Citation: BMC Medical Informatics and Decision Making 2006 6:37

    Content type: Research article

    Published on:

  40. A substantial proportion of microbiological screening in diagnostic laboratories is due to suspected urinary tract infections (UTIs), yet approximately two thirds of urine samples typically yield negative cult...

    Authors: Ross J. Burton, Mahableshwar Albur, Matthias Eberl and Simone M. Cuff

    Citation: BMC Medical Informatics and Decision Making 2019 19:171

    Content type: Research article

    Published on:

  41. Capturing sentence semantics plays a vital role in a range of text mining applications. Despite continuous efforts on the development of related datasets and models in the general domain, both datasets and mod...

    Authors: Qingyu Chen, Jingcheng Du, Sun Kim, W. John Wilbur and Zhiyong Lu

    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 1):73

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 20 Supplement 1

  42. The Systematic Nomenclature of Medicine Clinical Terms (SNOMED CT) is being advocated as the foundation for encoding clinical documentation. While the electronic medical record is likely to play a critical rol...

    Authors: Prakash M Nadkarni and Jonathan D Darer

    Citation: BMC Medical Informatics and Decision Making 2010 10:66

    Content type: Research article

    Published on:

  43. Pathology reports are written in free-text form, which precludes efficient data gathering. We aimed to overcome this limitation and design an automated system for extracting biomarker profiles from accumulated...

    Authors: Jeongeun Lee, Hyun-Je Song, Eunsil Yoon, Seong-Bae Park, Sung-Hye Park, Jeong-Wook Seo, Peom Park and Jinwook Choi

    Citation: BMC Medical Informatics and Decision Making 2018 18:29

    Content type: Research article

    Published on:

  44. Advanced mobile communications and portable computation are now combined in handheld devices called “smartphones”, which are also capable of running third-party software. The number of smartphone users is grow...

    Authors: Abu Saleh Mohammad Mosa, Illhoi Yoo and Lincoln Sheets

    Citation: BMC Medical Informatics and Decision Making 2012 12:67

    Content type: Research article

    Published on:

  45. Translational research typically requires data abstracted from medical records as well as data collected specifically for research. Unfortunately, many data within electronic health records are represented as ...

    Authors: Monique Hinchcliff, Eric Just, Sofia Podlusky, John Varga, Rowland W Chang and Warren A Kibbe

    Citation: BMC Medical Informatics and Decision Making 2012 12:106

    Content type: Correspondence

    Published on:

  46. Entity recognition is one of the most primary steps for text analysis and has long attracted considerable attention from researchers. In the clinical domain, various types of entities, such as clinical entities a...

    Authors: Zengjian Liu, Ming Yang, Xiaolong Wang, Qingcai Chen, Buzhou Tang, Zhe Wang and Hua Xu

    Citation: BMC Medical Informatics and Decision Making 2017 17(Suppl 2):67

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 17 Supplement 2

  47. The use of PubMed to answer daily medical care questions is limited because it is challenging to retrieve a small set of relevant articles and time is restricted. Knowing what aspects of queries are likely to ...

    Authors: Arjen Hoogendam, Anton FH Stalenhoef, Pieter F de Vries Robbé and A John PM Overbeke

    Citation: BMC Medical Informatics and Decision Making 2008 8:42

    Content type: Research article

    Published on:

  48. To detect attributes of medical concepts in clinical text, a traditional method often consists of two steps: named entity recognition of attributes and then relation classification between medical concepts and...

    Authors: Jun Xu, Zhiheng Li, Qiang Wei, Yonghui Wu, Yang Xiang, Hee-Jin Lee, Yaoyun Zhang, Stephen Wu and Hua Xu

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):236

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 19 Supplement 5

  49. The use of clinical data in electronic health records for machine-learning or data analytics depends on the conversion of free text into machine-readable codes. We have examined the feasibility of capturing th...

    Authors: Daniel B. Hier and Steven U. Brint

    Citation: BMC Medical Informatics and Decision Making 2020 20:47

    Content type: Research article

    Published on: