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  1. Knee injury and Osteoarthritis Outcome Score (KOOS) is an instrument used to quantify patients’ perceptions about their knee condition and associated problems. It is administered as a 42-item closed-ended ques...

    Authors: Irena Spasić, David Owen, Andrew Smith and Kate Button

    Citation: Journal of Biomedical Semantics 2019 10(Suppl 1):24

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 10 Supplement 1

  2. With the improvements to text mining technology and the availability of large unstructured Electronic Healthcare Records (EHR) datasets, it is now possible to extract structured information from raw text conta...

    Authors: Beatrice Alex, Claire Grover, Richard Tobin, Cathie Sudlow, Grant Mair and William Whiteley

    Citation: Journal of Biomedical Semantics 2019 10(Suppl 1):23

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 10 Supplement 1

  3. Deep Learning opens up opportunities for routinely scanning large bodies of biomedical literature and clinical narratives to represent the meaning of biomedical and clinical terms. However, the validation and ...

    Authors: Mercedes Arguello-Casteleiro, Robert Stevens, Julio Des-Diz, Chris Wroe, Maria Jesus Fernandez-Prieto, Nava Maroto, Diego Maseda-Fernandez, George Demetriou, Simon Peters, Peter-John M. Noble, Phil H. Jones, Jo Dukes-McEwan, Alan D. Radford, John Keane and Goran Nenadic

    Citation: Journal of Biomedical Semantics 2019 10(Suppl 1):22

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 10 Supplement 1

  4. Significant amounts of health data are stored as free-text within clinical reports, letters, discharge summaries and notes. Busy clinicians have limited time to read such large amounts of free-text and are at ...

    Authors: Alicja Piotrkowicz, Owen Johnson and Geoff Hall

    Citation: Journal of Biomedical Semantics 2019 10(Suppl 1):21

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 10 Supplement 1

  5. Free text in electronic health records (EHR) may contain additional phenotypic information beyond structured (coded) information. For major health events – heart attack and death – there is a lack of studies e...

    Authors: Anoop D. Shah, Emily Bailey, Tim Williams, Spiros Denaxas, Richard Dobson and Harry Hemingway

    Citation: Journal of Biomedical Semantics 2019 10(Suppl 1):20

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 10 Supplement 1

  6. There is an increasing amount of unstructured medical data that can be analysed for different purposes. However, information extraction from free text data may be particularly inefficient in the presence of sp...

    Authors: Hegler Tissot and Richard Dobson

    Citation: Journal of Biomedical Semantics 2019 10(Suppl 1):17

    Content type: Research

    Published on:

    This article is part of a Supplement: Volume 10 Supplement 1

  7. Readmission after discharge from a hospital is disruptive and costly, regardless of the reason. However, it can be particularly problematic for psychiatric patients, so predicting which patients may be readmit...

    Authors: Eben Holderness, Nicholas Miller, Philip Cawkwell, Kirsten Bolton, Marie Meteer, James Pustejovsky and Mei-Hua Hall

    Citation: Journal of Biomedical Semantics 2019 10:19

    Content type: Research

    Published on:

  8. Although the mouse is widely used to model human lung development, function, and disease, our understanding of the molecular mechanisms involved in alveolarization of the peripheral lung is incomplete. Recentl...

    Authors: Huaqin Pan, Gail H. Deutsch and Susan E. Wert

    Citation: Journal of Biomedical Semantics 2019 10:18

    Content type: Database

    Published on:

  11. Information in Electronic Health Records is largely stored as unstructured free text. Natural language processing (NLP), or Medical Language Processing (MLP) in medicine, aims at extracting structured informat...

    Authors: Martijn G. Kersloot, Francis Lau, Ameen Abu-Hanna, Derk L. Arts and Ronald Cornet

    Citation: Journal of Biomedical Semantics 2019 10:14

    Content type: Research

    Published on:

  12. Microbial genetics has formed a foundation for understanding many aspects of biology. Systematic annotation that supports computational data mining should reveal further insights for microbes, microbiomes, and...

    Authors: Deborah A. Siegele, Sandra A. LaBonte, Peter I-Fan Wu, Marcus C. Chibucos, Suvarna Nandendla, Michelle G. Giglio and James C. Hu

    Citation: Journal of Biomedical Semantics 2019 10:13

    Content type: Research

    Published on:

  14. To improve the outcomes of biological pathway analysis, a better way of integrating pathway data is needed. Ontologies can be used to organize data from disparate sources, and we leverage the Pathway Ontology ...

    Authors: Lucy Lu Wang, G. Thomas Hayman, Jennifer R. Smith, Monika Tutaj, Mary E. Shimoyama and John H. Gennari

    Citation: Journal of Biomedical Semantics 2019 10:11

    Content type: Research

    Published on:

  15. We introduce TranScriptML, a semantic representation schema for prescription regimens allowing various properties of prescriptions (e.g. dose, frequency, route) to be specified separately and applied (manually or...

    Authors: John Aberdeen, Samuel Bayer, Cheryl Clark, Meredith Keybl and David Tresner-Kirsch

    Citation: Journal of Biomedical Semantics 2019 10:10

    Content type: Research

    Published on:

  16. The vigilant observation of medical devices during post-market surveillance (PMS) for identifying safety-relevant incidents is a non-trivial task. A wide range of sources has to be monitored in order to integr...

    Authors: Alexandr Uciteli, Stefan Kropf, Timo Weiland, Stefanie Meese, Klaus Graef, Sabrina Rohrer, Marc O. Schurr, Wolfram Bartussek, Christoph Goller, Philipp Blohm, Robin Seidel, Christian Bayer, Manuel Kernenbach, Kathrin Pfeiffer, Wolfgang Lauer, Jörg-Uwe Meyer…

    Citation: Journal of Biomedical Semantics 2019 10:9

    Content type: Research

    Published on:

  17. The ability to express the same meaning in different ways is a well-known property of natural language. This amazing property is the source of major difficulties in natural language processing. Given the const...

    Authors: Oscar Lithgow-Serrano, Socorro Gama-Castro, Cecilia Ishida-Gutiérrez, Citlalli Mejía-Almonte, Víctor H. Tierrafría, Sara Martínez-Luna, Alberto Santos-Zavaleta, David Velázquez-Ramírez and Julio Collado-Vides

    Citation: Journal of Biomedical Semantics 2019 10:8

    Content type: Research

    Published on:

  19. Social risk factors are important dimensions of health and are linked to access to care, quality of life, health outcomes and life expectancy. However, in the Electronic Health Record, data related to many soc...

    Authors: Mike Conway, Salomeh Keyhani, Lee Christensen, Brett R. South, Marzieh Vali, Louise C. Walter, Danielle L. Mowery, Samir Abdelrahman and Wendy W. Chapman

    Citation: Journal of Biomedical Semantics 2019 10:6

    Content type: Software

    Published on:

  22. A Cardiac-centered Frailty Ontology can be an important foundation for using NLP to assess patient frailty. Frailty is an important consideration when making patient treatment decisions, particularly in older ...

    Authors: Kristina Doing-Harris, Bruce E. Bray, Anne Thackeray, Rashmee U. Shah, Yijun Shao, Yan Cheng, Qing Zeng-Treitler, Jennifer H. Garvin and Charlene Weir

    Citation: Journal of Biomedical Semantics 2019 10:3

    Content type: Research

    Published on:

  23. VerbNet, an extensive computational verb lexicon for English, has proved useful for supporting a wide range of Natural Language Processing tasks requiring information about the behaviour and meaning of verbs. ...

    Authors: Billy Chiu, Olga Majewska, Sampo Pyysalo, Laura Wey, Ulla Stenius, Anna Korhonen and Martha Palmer

    Citation: Journal of Biomedical Semantics 2019 10:2

    Content type: Database

    Published on:

  25. Structured electronic health records are a rich resource for identifying novel correlations, such as co-morbidities and adverse drug reactions. For drug development and better understanding of biomedical pheno...

    Authors: Thomas C. Rindflesch, Catherine L. Blake, Michael J. Cairelli, Marcelo Fiszman, Caroline J. Zeiss and Halil Kilicoglu

    Citation: Journal of Biomedical Semantics 2018 9:25

    Content type: Research

    Published on:

  26. Even though several high-quality clinical terminologies, such as SNOMED CT and LOINC, are readily available, uptake in clinical systems has been slow and many continue to capture information in plain text or u...

    Authors: Alejandro Metke-Jimenez, Jim Steel, David Hansen and Michael Lawley

    Citation: Journal of Biomedical Semantics 2018 9:24

    Content type: Software

    Published on:

  27. Biomedical knowledge graphs have become important tools to computationally analyse the comprehensive body of biomedical knowledge. They represent knowledge as subject-predicate-object triples, in which the pre...

    Authors: Wytze J. Vlietstra, Rein Vos, Anneke M. Sijbers, Erik M. van Mulligen and Jan A. Kors

    Citation: Journal of Biomedical Semantics 2018 9:23

    Content type: Research

    Published on:

  28. In this paper, we discuss the design and development of a formal ontology to describe misinformation about vaccines. Vaccine misinformation is one of the drivers leading to vaccine hesitancy in patients. While...

    Authors: Muhammad Amith and Cui Tao

    Citation: Journal of Biomedical Semantics 2018 9:22

    Content type: Research

    Published on:

  29. While representation learning techniques have shown great promise in application to a number of different NLP tasks, they have had little impact on the problem of ontology matching. Unlike past work that has f...

    Authors: Prodromos Kolyvakis, Alexandros Kalousis, Barry Smith and Dimitris Kiritsis

    Citation: Journal of Biomedical Semantics 2018 9:21

    Content type: Research

    Published on:

  30. Entropy has become increasingly popular in computer science and information theory because it can be used to measure the predictability and redundancy of knowledge bases, especially ontologies. However, curren...

    Authors: Ying Shen, Daoyuan Chen, Buzhou Tang, Min Yang and Kai Lei

    Citation: Journal of Biomedical Semantics 2018 9:20

    Content type: Research

    Published on:

  31. Vaccine has been one of the most successful public health interventions to date. However, vaccines are pharmaceutical products that carry risks so that many adverse events (AEs) are reported after receiving va...

    Authors: Junxiang Wang, Liang Zhao, Yanfang Ye and Yuji Zhang

    Citation: Journal of Biomedical Semantics 2018 9:19

    Content type: Research

    Published on:

  32. In recent years, Twitter has been applied to monitor diseases through its facility to monitor users’ comments and concerns in real-time. The analysis of tweets for disease mentions should reflect not only user...

    Authors: Joana M. Barros, Jim Duggan and Dietrich Rebholz-Schuhmann

    Citation: Journal of Biomedical Semantics 2018 9:18

    Content type: Research

    Published on:

  33. Adverse drug reactions (ADRs), also called as drug adverse events (AEs), are reported in the FDA drug labels; however, it is a big challenge to properly retrieve and analyze the ADRs and their potential relati...

    Authors: Junguk Hur, Arzucan Özgür and Yongqun He

    Citation: Journal of Biomedical Semantics 2018 9:17

    Content type: Research

    Published on:

  34. Legacy data and new structured data can be stored in a standardized format as XML-based EHRs on XML databases. Querying documents on these databases is crucial for answering research questions. Instead of usin...

    Authors: Stefan Kropf, Alexandr Uciteli, Katrin Schierle, Peter Krücken, Kerstin Denecke and Heinrich Herre

    Citation: Journal of Biomedical Semantics 2018 9:16

    Content type: Research

    Published on:

  35. Prompted by the frequency of concomitant use of prescription drugs with natural products, and the lack of knowledge regarding the impact of pharmacokinetic-based natural product-drug interactions (PK-NPDIs), t...

    Authors: John Judkins, Jessica Tay-Sontheimer, Richard D. Boyce and Mathias Brochhausen

    Citation: Journal of Biomedical Semantics 2018 9:15

    Content type: Research

    Published on:

  36. Inherited mutations in glyco-related genes can affect the biosynthesis and degradation of glycans and result in severe genetic diseases and disorders. The Glyco-Disease Genes Database (GDGDB), which provides i...

    Authors: Elena Solovieva, Toshihide Shikanai, Noriaki Fujita and Hisashi Narimatsu

    Citation: Journal of Biomedical Semantics 2018 9:14

    Content type: Research

    Published on:

  37. Automatic identification of term variants or acceptable alternative free-text terms for gene and protein names from the millions of biomedical publications is a challenging task. Ontologies, such as the Cardio...

    Authors: Mercedes Arguello Casteleiro, George Demetriou, Warren Read, Maria Jesus Fernandez Prieto, Nava Maroto, Diego Maseda Fernandez, Goran Nenadic, Julie Klein, John Keane and Robert Stevens

    Citation: Journal of Biomedical Semantics 2018 9:13

    Content type: Research

    Published on:

  38. Natural language processing applied to clinical text or aimed at a clinical outcome has been thriving in recent years. This paper offers the first broad overview of clinical Natural Language Processing (NLP) f...

    Authors: Aurélie Névéol, Hercules Dalianis, Sumithra Velupillai, Guergana Savova and Pierre Zweigenbaum

    Citation: Journal of Biomedical Semantics 2018 9:12

    Content type: Review

    Published on:

  39. The goal of ontology matching is to identify correspondences between entities from different yet overlapping ontologies so as to facilitate semantic integration, reuse and interoperability. As a well developed...

    Authors: Mengyi Zhao, Songmao Zhang, Weizhuo Li and Guowei Chen

    Citation: Journal of Biomedical Semantics 2018 9:11

    Content type: Research

    Published on:

  40. The Gene Ontology (GO) consists of over 40,000 terms for biological processes, cell components and gene product activities linked into a graph structure by over 90,000 relationships. It has been used to annota...

    Authors: David J. Osumi-Sutherland, Enrico Ponta, Melanie Courtot, Helen Parkinson and Laura Badi

    Citation: Journal of Biomedical Semantics 2018 9:10

    Content type: Research

    Published on:

  41. Pathogenesis of inflammatory diseases can be tracked by studying the causality relationships among the factors contributing to its development. We could, for instance, hypothesize on the connections of the pat...

    Authors: Asan Agibetov, Ernesto Jiménez-Ruiz, Marta Ondrésik, Alessandro Solimando, Imon Banerjee, Giovanna Guerrini, Chiara E. Catalano, Joaquim M. Oliveira, Giuseppe Patanè, Rui L. Reis and Michela Spagnuolo

    Citation: Journal of Biomedical Semantics 2018 9:9

    Content type: Research

    Published on:

  42. Treatment of type 2 diabetes mellitus (T2DM) is a complex problem. A clinical decision support system (CDSS) based on massive and distributed electronic health record data can facilitate the automation of this...

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

    Citation: Journal of Biomedical Semantics 2018 9:8

    Content type: Research

    Published on:

  43. Relation extraction from biomedical publications is an important task in the area of semantic mining of text. Kernel methods for supervised relation extraction are often preferred over manual feature engineeri...

    Authors: Nagesh C. Panyam, Karin Verspoor, Trevor Cohn and Kotagiri Ramamohanarao

    Citation: Journal of Biomedical Semantics 2018 9:7

    Content type: Research

    Published on:

  45. The biodiversity domain, and in particular biological taxonomy, is moving in the direction of semantization of its research outputs. The present work introduces OpenBiodiv-O, the ontology that serves as the ba...

    Authors: Viktor Senderov, Kiril Simov, Nico Franz, Pavel Stoev, Terry Catapano, Donat Agosti, Guido Sautter, Robert A. Morris and Lyubomir Penev

    Citation: Journal of Biomedical Semantics 2018 9:5

    Content type: Research

    Published on:

  46. Biomedical ontologies pose several challenges to ontology matching due both to the complexity of the biomedical domain and to the characteristics of the ontologies themselves. The biomedical tracks in the Onto...

    Authors: Daniel Faria, Catia Pesquita, Isabela Mott, Catarina Martins, Francisco M. Couto and Isabel F. Cruz

    Citation: Journal of Biomedical Semantics 2018 9:4

    Content type: Research

    Published on:

  47. Ontologies are critical to data/metadata and knowledge standardization, sharing, and analysis. With hundreds of biological and biomedical ontologies developed, it has become critical to ensure ontology interop...

    Authors: Yongqun He, Zuoshuang Xiang, Jie Zheng, Yu Lin, James A. Overton and Edison Ong

    Citation: Journal of Biomedical Semantics 2018 9:3

    Content type: Review

    Published on:

  48. Traditionally text mention normalization corpora have normalized concepts to single ontology identifiers (“pre-coordinated concepts”). Less frequently, normalization corpora have used concepts with multiple id...

    Authors: John D. Osborne, Matthew B. Neu, Maria I. Danila, Thamar Solorio and Steven J. Bethard

    Citation: Journal of Biomedical Semantics 2018 9:2

    Content type: Research

    Published on:

  50. Integration and analysis of phenotype data from humans and model organisms is a key challenge in building our understanding of normal biology and pathophysiology. However, the range of phenotypes and anatomica...

    Authors: Miguel Ángel Rodríguez-García, Georgios V. Gkoutos, Paul N. Schofield and Robert Hoehndorf

    Citation: Journal of Biomedical Semantics 2017 8:58

    Content type: Research

    Published on:

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Journal of Biomedical Semantics

ISSN: 2041-1480