Skip to main content

Articles

Page 2 of 11

  1. Incorporating the feedback of expert stakeholders in ontology development is important to ensure content is appropriate, comprehensive, meets community needs and is interoperable with other ontologies and clas...

    Authors: Emma Norris, Janna Hastings, Marta M. Marques, Ailbhe N. Finnerty Mutlu, Silje Zink and Susan Michie
    Citation: Journal of Biomedical Semantics 2021 12:4
  2. Mortality prediction is an important task to achieve smart healthcare, especially for the management of intensive care unit. It can provide a reference for doctors to quickly predict the course of disease and ...

    Authors: Haiyang Yang, Li Kuang and FengQiang Xia
    Citation: Journal of Biomedical Semantics 2021 12:3
  3. Accurate and precise information about the therapeutic uses (indications) of a drug is essential for applications in drug repurposing and precision medicine. Leading online drug resources such as DrugCentral a...

    Authors: Kody Moodley, Linda Rieswijk, Tudor I. Oprea and Michel Dumontier
    Citation: Journal of Biomedical Semantics 2021 12:2
  4. Population-based cancer registries constitute an important information source in cancer epidemiology. Studies collating and comparing data across regional and national boundaries have proved important for depl...

    Authors: Nicholas Charles Nicholson, Francesco Giusti, Manola Bettio, Raquel Negrao Carvalho, Nadya Dimitrova, Tadeusz Dyba, Manuela Flego, Luciana Neamtiu, Giorgia Randi and Carmen Martos
    Citation: Journal of Biomedical Semantics 2021 12:1
  5. The successful determination and analysis of phenotypes plays a key role in the diagnostic process, the evaluation of risk factors and the recruitment of participants for clinical and epidemiological studies. ...

    Authors: Alexandr Uciteli, Christoph Beger, Toralf Kirsten, Frank A. Meineke and Heinrich Herre
    Citation: Journal of Biomedical Semantics 2020 11:15
  6. Free-text descriptions in electronic health records (EHRs) can be of interest for clinical research and care optimization. However, free text cannot be readily interpreted by a computer and, therefore, has lim...

    Authors: Martijn G. Kersloot, Florentien J. P. van Putten, Ameen Abu-Hanna, Ronald Cornet and Derk L. Arts
    Citation: Journal of Biomedical Semantics 2020 11:14
  7. The Genetic and Rare Diseases (GARD) Information Center was established by the National Institutes of Health (NIH) to provide freely accessible consumer health information on over 6500 genetic and rare disease...

    Authors: Qian Zhu, Dac-Trung Nguyen, Ivan Grishagin, Noel Southall, Eric Sid and Anne Pariser
    Citation: Journal of Biomedical Semantics 2020 11:13
  8. Medical knowledge is accumulated in scientific research papers along time. In order to exploit this knowledge by automated systems, there is a growing interest in developing text mining methodologies to extrac...

    Authors: Patricio Wolff, Sebastián Ríos, David Clavijo, Manuel Graña and Miguel Carrasco
    Citation: Journal of Biomedical Semantics 2020 11:12
  9. Recently, more electronic data sources are becoming available in the healthcare domain. Electronic health records (EHRs), with their vast amounts of potentially available data, can greatly improve healthcare. ...

    Authors: Kohei Kajiyama, Hiromasa Horiguchi, Takashi Okumura, Mizuki Morita and Yoshinobu Kano
    Citation: Journal of Biomedical Semantics 2020 11:11
  10. Up to 35% of nurses’ working time is spent on care documentation. We describe the evaluation of a system aimed at assisting nurses in documenting patient care and potentially reducing the documentation workloa...

    Authors: Hans Moen, Kai Hakala, Laura-Maria Peltonen, Hanna-Maria Matinolli, Henry Suhonen, Kirsi Terho, Riitta Danielsson-Ojala, Maija Valta, Filip Ginter, Tapio Salakoski and Sanna Salanterä
    Citation: Journal of Biomedical Semantics 2020 11:10
  11. Knowledge graphs can represent the contents of biomedical literature and databases as subject-predicate-object triples, thereby enabling comprehensive analyses that identify e.g. relationships between diseases...

    Authors: Wytze J. Vlietstra, Rein Vos, Marjan van den Akker, Erik M. van Mulligen and Jan A. Kors
    Citation: Journal of Biomedical Semantics 2020 11:9
  12. A key challenge for improving the quality of health care is to be able to use a common framework to work with patient information acquired in any of the health and life science disciplines. Patient information...

    Authors: William D. Duncan, Thankam Thyvalikakath, Melissa Haendel, Carlo Torniai, Pedro Hernandez, Mei Song, Amit Acharya, Daniel J. Caplan, Titus Schleyer and Alan Ruttenberg
    Citation: Journal of Biomedical Semantics 2020 11:8
  13. Textual corpora are extremely important for various NLP applications as they provide information necessary for creating, setting and testing those applications and the corresponding tools. They are also crucia...

    Authors: Natalia Grabar, Clément Dalloux and Vincent Claveau
    Citation: Journal of Biomedical Semantics 2020 11:7
  14. Sharing sensitive data across organizational boundaries is often significantly limited by legal and ethical restrictions. Regulations such as the EU General Data Protection Rules (GDPR) impose strict requireme...

    Authors: Lars Christoph Gleim, Md Rezaul Karim, Lukas Zimmermann, Oliver Kohlbacher, Holger Stenzhorn, Stefan Decker and Oya Beyan
    Citation: Journal of Biomedical Semantics 2020 11:6
  15. Health 2.0 allows patients and caregivers to conveniently seek medical information and advice via e-portals and online discussion forums, especially regarding potential drug side effects. Although online healt...

    Authors: Van-Hoang Nguyen, Kazunari Sugiyama, Min-Yen Kan and Kishaloy Halder
    Citation: Journal of Biomedical Semantics 2020 11:5
  16. Most tutorial ontologies focus on illustrating one aspect of ontology development, notably language features and automated reasoners, but ignore ontology development factors, such as emergent modelling guideli...

    Authors: C. Maria Keet
    Citation: Journal of Biomedical Semantics 2020 11:4
  17. Scientific activity for 3D bioprinting has increased over the past years focusing mainly on fully functional biological constructs to overcome issues related to organ transplants. This research performs a scie...

    Authors: Leonardo Azael GarcĂ­a-GarcĂ­a and Marisela RodrĂ­guez-Salvador
    Citation: Journal of Biomedical Semantics 2020 11:3
  18. Duration of untreated psychosis (DUP) is an important clinical construct in the field of mental health, as longer DUP can be associated with worse intervention outcomes. DUP estimation requires knowledge about wh...

    Authors: Natalia Viani, Joyce Kam, Lucia Yin, André Bittar, Rina Dutta, Rashmi Patel, Robert Stewart and Sumithra Velupillai
    Citation: Journal of Biomedical Semantics 2020 11:2
  19. Ontologies are widely used across biology and biomedicine for the annotation of databases. Ontology development is often a manual, time-consuming, and expensive process. Automatic or semi-automatic identificat...

    Authors: Sara Althubaiti, Ĺženay Kafkas, Marwa Abdelhakim and Robert Hoehndorf
    Citation: Journal of Biomedical Semantics 2020 11:1
  20. Host-microbiome interactions (HMIs) are critical for the modulation of biological processes and are associated with several diseases. Extensive HMI studies have generated large amounts of data. We propose that...

    Authors: Yongqun He, Haihe Wang, Jie Zheng, Daniel P. Beiting, Anna Maria Masci, Hong Yu, Kaiyong Liu, Jianmin Wu, Jeffrey L. Curtis, Barry Smith, Alexander V. Alekseyenko and Jihad S. Obeid
    Citation: Journal of Biomedical Semantics 2019 10:25
  21. 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

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

  22. 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

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

  23. 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

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

  24. 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

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

  25. 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

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

  26. 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

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

  27. 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
  28. 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
  29. 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
  30. 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
  31. 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
  32. 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
  33. 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
  34. 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
  35. 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
  36. 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
  37. 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
  38. 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
  39. 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
  40. 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
  41. 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
  42. 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
  43. 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

Annual Journal Metrics