bims-librar Biomed News
on Biomedical librarianship
Issue of 2019‒07‒21
eleven papers selected by
Thomas Krichel
Open Library Society

  1. Foot Ankle Surg. 2019 Jul 08. pii: S1268-7731(19)30106-7. [Epub ahead of print]
    Richter M.
  2. Nature. 2019 Jul;571(7765): 316-318
    Pulla P.
    Keywords:  Computer science; Databases; Developing world; Publishing
  3. Genomics Inform. 2019 Jun;17(2): e19
    Eckart de Castilho R, Ide N, Kim JD, Klie JC, Suderman K.
      In this paper we investigate cross-platform interoperability for natural language processing (NLP) and, in particular, annotation of textual resources, with an eye toward identifying the design elements of annotation models and processes that are particularly problematic for, or amenable to, enabling seamless communication across different platforms. The study is conducted in the context of a specific annotation methodology, namely machine-assisted interactive annotation (also known as human-in-the-loop annotation). This methodology requires the ability to freely combine resources from different document repositories, access a wide array of NLP tools that automatically annotate corpora for various linguistic phenomena, and use a sophisticated annotation editor that enables interactive manual annotation coupled with on-the-fly machine learning. We consider three independently developed platforms, each of which utilizes a different model for representing annotations over text, and each of which performs a different role in the process.
    Keywords:  annotation software; biomedical text mining; interoperability
  4. Genomics Inform. 2019 Jun;17(2): e16
    Tateisi Y.
      Medical Subject Headings (MeSH), a medical thesaurus created by the National Library of Medicine (NLM), is a useful resource for natural language processing (NLP). In this article, the current status of the Japanese version of Medical Subject Headings (MeSH) is reviewed. Online investigation found that Japanese-English dictionaries, which assign MeSH information to applicable terms, but use them for NLP, were found to be difficult to access, due to license restrictions. Here, we investigate an open-source Japanese-English glossary as an alternative method for assigning MeSH IDs to Japanese terms, to obtain preliminary data for NLP proof-of-concept.
    Keywords:  Japanese language resource; MeSH; medical vocabulary
  5. BMC Public Health. 2019 Jul 16. 19(1): 952
    Li M, Yan S, Yang D, Li B, Cui W.
      BACKGROUND: YouTube™ ( ), as a very popular video site around the world, is increasingly being used for health information. The objectives of this review were to assess the overall usefulness of information on food poisoning presented on YouTube™ for patients.METHODS: The YouTube™ website was systematically searched using the key words "food poisoning", "foodborne diseases" and "foodborne illness". One hundred and sixty videos meet the inclusion criteria. Two independent reviewers scored the videos utilizing a customized usefulness scoring scheme separately and assessed the video duration, views, days since upload, likes, and dislikes. The videos were categorized as education, entertainment, News & Politics and People & Blogs. A usefulness score was devised to assess video quality and to categorize the videos into "slightly useful", "useful", and "very useful".
    RESULTS: Most videos were educational 66 (41.3%). Educational videos had significantly higher scores, but had no significant differences in likes, views or views/day. Over half of the videos (97/160) were categorized as "useful". The mean posted days (885.2 ± 756.1 vs 1338.0 ± 887.0, P = 0.043) and the mean duration of video (12.8 ± 13.9 vs 3.5 ± 3.4, P < 0.001) were both significantly different in the very useful group compared with the slightly useful group. There was no correlation between usefulness and the number of likes, the number of dislikes, the number of views, or views/day.
    CONCLUSION: YouTube™ is a promising source of information regarding food poisoning. Educational videos are of highest usefulness. Considering that there is a lot of low-credibility information, consumers need to be guided to reliable videos in the field of healthcare information.
    Keywords:  Epidemiology; Food poisoning; Foodborne diseases; Foodborne illness
  6. Front Public Health. 2019 ;7 178
    Aschbrenner KA, Naslund JA, Tomlinson EF, Kinney A, Pratt SI, Brunette MF.
      Objective: Youth with mental illnesses often engage in unhealthy behaviors associated with early mortality from physical diseases in adulthood, but interventions to support positive health behaviors are rarely offered as part of routine mental health care for this group. Digital health technology that is desirable, accessible, and affordable has the potential to address health behaviors in public mental health settings where many adolescents with severe mental health problems receive care. The aims of this study were to examine how adolescents receiving public mental health services use digital technology and social media and to explore their preferences using technology to support health and wellness. Methods: Using a convergent parallel mixed methods design, we surveyed adolescents ages 13-18 from four community mental health centers in one state and conducted focus group interviews to explore their perspectives on using digital technology and social media to receive health coaching and connect with peers to support healthy behaviors. The survey and focus group data were merged to inform the future development of a digital health intervention for adolescents receiving public mental health services. Results: Of 121 survey respondents (mean age 15.2, SD = 1.5), 92% had a cell phone, 79% had a smartphone, 90% used text messaging, and 98% used social media. Focus group interviews revealed that adolescents were interested in receiving strengths-based mobile health coaching, and they preferred structured online peer-to-peer interactions in which a professional moderator promotes positive connections and adherence to privacy guidelines. Conclusions: Adolescents receiving public mental health services in this study had access to smartphones and were frequent social media users. These data suggest that digital health interventions to promote health and wellness among adolescents may be scalable in community mental health settings. Adolescent participants suggested that digital health interventions for this group should focus on strengths and online peer support for health promotion should include a professional moderator to foster and manage peer-to-peer interactions.
    Keywords:  adolescents; digital health interventions; health promotion; mental illness; mobile health coaching; peer-to-peer support; social media
  7. Pediatr Blood Cancer. 2019 Jul 19. e27931
    Grace JG, Schweers L, Anazodo A, Freyer DR.
      Adolescents and young adults (AYAs, 15-39 years old) are an ideal population to benefit from the ever-expanding number and variety of cancer information and health resources available via the Internet and other digital platforms. However, the ability of individual AYAs to fully utilize such resources depends on their degree of health literacy. Across the trajectory of cancer care, an important role for the oncology clinician is assisting AYAs and caregivers in accessing quality health information consistent with their level of health literacy. Working from the premise that all AYAs with cancer and their caregivers deserve to be empowered with maximal knowledge about their condition, this review provides information to assist oncology clinicians in (1) understanding the variety of contemporary online resources that are currently available, including their strengths and limitations; (2) evaluating the quality of health information; and (3) recommending specific health information resources to their AYA patients.
    Keywords:  adolescent and young adult; health communication; health education; health information; health literacy; health promotion; patient education
  8. PLoS One. 2019 ;14(7): e0219389
    Lee SY.
      We propose a new method for vectorizing a document using the relational characteristics of the words in the document. For the relational characteristics, we use two types of relational information of a word: 1) the centrality measures of the word and 2) the number of times that the word is used with other words in the document. We propose these methods mainly because information regarding the relations of a word to other words in the document are likely to better represent the unique characteristics of the document than the frequency-based methods (e.g., term frequency and term frequency-inverse document frequency). In experiments using a corpus consisting of 14 documents pertaining to four different topics, the results of clustering analysis using cosine similarities between vectors of relational information for words were comparable to (and more accurate than in some cases) those obtained using vectors of frequency-based methods. The clustering analysis using vectors of tie weights between words yielded the most accurate result. Although the results obtained for the small dataset used in this study can hardly be generalized, they suggest that at least in some cases, vectorization of a document using the relational characteristics of the words can provide more accurate results than the frequency-based vectors.
  9. NPJ Digit Med. 2019 ;2 22
    Monroy GL, Won J, Dsouza R, Pande P, Hill MC, Porter RG, Novak MA, Spillman DR, Boppart SA.
      The diagnosis and treatment of otitis media (OM), a common childhood infection, is a significant burden on the healthcare system. Diagnosis relies on observer experience via otoscopy, although for non-specialists or inexperienced users, accurate diagnosis can be difficult. In past studies, optical coherence tomography (OCT) has been used to quantitatively characterize disease states of OM, although with the involvement of experts to interpret and correlate image-based indicators of infection with clinical information. In this paper, a flexible and comprehensive framework is presented that automatically extracts features from OCT images, classifies data, and presents clinically relevant results in a user-friendly platform suitable for point-of-care and primary care settings. This framework was used to test the discrimination between OCT images of normal controls, ears with biofilms, and ears with biofilms and middle ear fluid (effusion). Predicted future performance of this classification platform returned promising results (90%+ accuracy) in various initial tests. With integration into patient healthcare workflow, users of all levels of medical experience may be able to collect OCT data and accurately identify the presence of middle ear fluid and/or biofilms.
    Keywords:  Biomedical engineering; Imaging and sensing; Machine learning; Paediatric research; Translational research
  10. Genomics Inform. 2019 Jun;17(2): e14
    Garcia L, Giraldo O, Garcia A, Rebholz-Schuhmann D.
      The total number of scholarly publications grows day by day, making it necessary to explore and use simple yet effective ways to expose their metadata. supports adding structured metadata to web pages via markup, making it easier for data providers but also for search engines to provide the right search results. Bioschemas is based on the standards of, providing new types, properties and guidelines for metadata, i.e., providing metadata profiles tailored to the Life Sciences domain. Here we present our proposed contribution to Bioschemas (from the project "Biotea"), which supports metadata contributions for scholarly publications via profiles and web components. Biotea comprises a semantic model to represent publications together with annotated elements recognized from the scientific text; our Biotea model has been mapped to following Bioschemas standards.
    Keywords:  biomedical text mining; literature metadata; semantic annotations; structured data; web page markup