Special Issue "Curative Power of Medical Data"

A special issue of Data (ISSN 2306-5729).

Deadline for manuscript submissions: closed (30 September 2018) | Viewed by 8696

Special Issue Editors

Dr. Diana Trandabat
E-Mail Website
Guest Editor
Faculty of Computer Science, "Alexandru Ioan Cuza" University, 700057 Iaşi, Romania
Dr. Daniela Gîfu
E-Mail Website
Guest Editor
1. Faculty of Computer Science, "Alexandru Ioan Cuza" University of Iași, 700057 Iaşi, Romania
2. Institute of Computer Science, Romanian Academy - Iași branch, 700481 Iaşi, Romania
Dr. Kevin Cohen
E-Mail Website
Guest Editor
University of Colorado School of Medicine, Aurora, CO, USA
Interests: spinal cord injury and regeneration; analysis of the speech of suicidal individuals; temporality in health records; information extraction from epilepsy clinic notes
Special Issues, Collections and Topics in MDPI journals
Dr. Jingbo Xia
E-Mail Website
Guest Editor
Department of Big data science, College of Informatics, Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural University, Wuhan 430070, China
Interests: BioNLP; data mining; bioinformatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In an era where massive amounts of medical data are available, researchers working in biological, biomedical, and clinical domains have increasingly started to require the help of language engineers to process large quantities of biomedical and molecular biology literature (such as PubMed), patient data, or health records. Linking the contents of these documents to each other, as well as to specialized ontologies, could enable access to, and discovery of, structured clinical information and foster a major leap in natural language processing and health research.

MEDA-2018 aims to gather innovative approaches for the exploitation of biomedical data using semantic web technologies and linked data by bringing together practitioners, researchers, and scholars to share examples, use cases, theories and analysis of biomedical data. The main objective of this second edition workshop is to consolidate an internationally appreciated forum for scientific research in BioMed, with emphasis on crowdsourcing, semantic web, knowledge integration and data linking.

This Special Issue will contain the expanded versions of selected papers presented at the MEDA-2018 workshop (https://profs.info.uaic.ro/~meda/) of the ACM/IEEE Joint Conference on Digital Libraries (JCDL 2018) held in Fort Worth, Texas, USA, 3–6 June, 2018.

Dr. Diana Trandabat
Dr. Daniela Gîfu
Dr. Kevin Cohen
Dr. Jingbo Xia
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Data is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Crowdsourcing approaches in biomedicine
  • Collaborative computational technologies for biomedical research
  • Biomedical digital libraries
  • Mining biomedical literature
  • Event-based text mining for biology and related fields
  • Event and entity extraction in medical texts
  • Conceptual graphs extracted from medical texts
  • Annotation of semantic content, with applications in medicine and biology
  • Techniques for Big Data in Healthcare
  • Medical search engines
  • Distributed communication system in biomedical applications
  • Deep learning for bioinformatics
  • Biomedical question/answering
  • Biomedical topic modeling
  • Biomedical language systems
  • Text summarization in the biomedical domain

Published Papers (5 papers)

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Editorial
Special Issue on the Curative Power of Medical Data
1 Institute of Computer Science, Romanian Academy-Iasi branch, Iasi 700481, Romania
2 Faculty of Computer Science, Alexandru Ioan Cuza University of Iasi, Iași 700483, Romania
3 Cognos Business Consulting S.R.L., 7, Iuliu Maniu Blvd, Bucharest 061072, Romania
4 Computational Bioscience Program, University of Colorado School of Medicine, Aurora, CO 80045, USA
5 Department of Biostatistics, Huazhong Agricultural University, Wuhan 430070, China
Data 2019, 4(2), 85; https://doi.org/10.3390/data4020085 - 14 Jun 2019
Cited by 1 | Viewed by 1245
Abstract
With the massive amounts of medical data made available online, language technologies have proven to be indispensable in processing biomedical and molecular biology literature, health data or patient records. With huge amount of reports, evaluating their impact has long ceased to be a [...] Read more.
With the massive amounts of medical data made available online, language technologies have proven to be indispensable in processing biomedical and molecular biology literature, health data or patient records. With huge amount of reports, evaluating their impact has long ceased to be a trivial task. Linking the contents of these documents to each other, as well as to specialized ontologies, could enable access to and the discovery of structured clinical information and could foster a major leap in natural language processing and in health research. The aim of this Special Issue, “Curative Power of Medical Data” in Data, is to gather innovative approaches for the exploitation of biomedical data using semantic web technologies and linked data by developing a community involvement in biomedical research. This Special Issue contains four surveys, which include a wide range of topics, from the analysis of biomedical articles writing style, to automatically generating tests from medical references, constructing a Gold standard biomedical corpus or the visualization of biomedical data. Full article
(This article belongs to the Special Issue Curative Power of Medical Data)
Article
Towards Identifying Author Confidence in Biomedical Articles
1 Institute of Computer Science, Romanian Academy-Iasi branch, 700481 Iasi, Romania
2 Faculty of Computer Science, Alexandru Ioan Cuza University of Iasi, 700483 Iași, Romania
3 Cognos Business Consulting S.R.L., 7, Iuliu Maniu Blvd, 061072 Bucharest, Romania
Data 2019, 4(1), 18; https://doi.org/10.3390/data4010018 - 21 Jan 2019
Cited by 2 | Viewed by 1551
Abstract
In an era where the volume of medical literature is increasing daily, researchers in the biomedical and clinical areas have joined efforts with language engineers to analyze the large amount of biomedical and molecular biology literature (such as PubMed), patient data, or health [...] Read more.
In an era where the volume of medical literature is increasing daily, researchers in the biomedical and clinical areas have joined efforts with language engineers to analyze the large amount of biomedical and molecular biology literature (such as PubMed), patient data, or health records. With such a huge amount of reports, evaluating their impact has long stopped being a trivial task. In this context, this paper intended to introduce a non-scientific factor that represents an important element in gaining acceptance of claims. We postulated that the confidence that an author has in expressing their work plays an important role in shaping the first impression that influences the reader’s perception of the paper. The results discussed in this paper were based on a series of experiments that were ran using data from the open archives initiative (OAI) corpus, which provides interoperability standards to facilitate effective dissemination of the content. This method may be useful to the direct beneficiaries (i.e., authors, who are engaged in medical or academic research), but also, to the researchers in the fields of biomedical text mining (BioNLP) and NLP, etc. Full article
(This article belongs to the Special Issue Curative Power of Medical Data)
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Article
Medi-Test: Generating Tests from Medical Reference Texts
Faculty of Computer Science, “Alexandru Ioan Cuza” University of Iaşi, Iași 700483, Romania
Data 2018, 3(4), 70; https://doi.org/10.3390/data3040070 - 19 Dec 2018
Cited by 3 | Viewed by 1969
Abstract
The Medi-test system we developed was motivated by the large number of resources available for the medical domain, as well as the number of tests needed in this field (during and after the medical school) for evaluation, promotion, certification, etc. Generating questions to [...] Read more.
The Medi-test system we developed was motivated by the large number of resources available for the medical domain, as well as the number of tests needed in this field (during and after the medical school) for evaluation, promotion, certification, etc. Generating questions to support learning and user interactivity has been an interesting and dynamic topic in NLP since the availability of e-book curricula and e-learning platforms. Current e-learning platforms offer increased support for student evaluation, with an emphasis in exploiting automation in both test generation and evaluation. In this context, our system is able to evaluate a student’s academic performance for the medical domain. Using medical reference texts as input and supported by a specially designed medical ontology, Medi-test generates different types of questionnaires for Romanian language. The evaluation includes 4 types of questions (multiple-choice, fill in the blanks, true/false, and match), can have customizable length and difficulty, and can be automatically graded. A recent extension of our system also allows for the generation of tests which include images. We evaluated our system with a local testing team, but also with a set of medicine students, and user satisfaction questionnaires showed that the system can be used to enhance learning. Full article
(This article belongs to the Special Issue Curative Power of Medical Data)
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Article
Towards the Construction of a Gold Standard Biomedical Corpus for the Romanian Language
1 Romanian Academy Research Institute for Artificial Intelligence, 13 Calea 13 Septembrie, Bucharest 050711, Romania
2 National Institute of Diabetes and Metabolic Diseases “N.C. Paulescu”, 5-7 Ion Movilă Street, Bucharest 020475, Romania
These authors contributed equally to this work.
Data 2018, 3(4), 53; https://doi.org/10.3390/data3040053 - 23 Nov 2018
Cited by 3 | Viewed by 1455
Abstract
Gold standard corpora (GSCs) are essential for the supervised training and evaluation of systems that perform natural language processing (NLP) tasks. Currently, most of the resources used in biomedical NLP tasks are mainly in English. Little effort has been reported for other languages [...] Read more.
Gold standard corpora (GSCs) are essential for the supervised training and evaluation of systems that perform natural language processing (NLP) tasks. Currently, most of the resources used in biomedical NLP tasks are mainly in English. Little effort has been reported for other languages including Romanian and, thus, access to such language resources is poor. In this paper, we present the construction of the first morphologically and terminologically annotated biomedical corpus of the Romanian language (MoNERo), meant to serve as a gold standard for biomedical part-of-speech (POS) tagging and biomedical named entity recognition (bioNER). It contains 14,012 tokens distributed in three medical subdomains: cardiology, diabetes and endocrinology, extracted from books, journals and blogposts. In order to automatically annotate the corpus with POS tags, we used a Romanian tag set which has 715 labels, while diseases, anatomy, procedures and chemicals and drugs labels were manually annotated for bioNER with a Cohen Kappa coefficient of 92.8% and revealed the occurrence of 1877 medical named entities. The automatic annotation of the corpus has been manually checked. The corpus is publicly available and can be used to facilitate the development of NLP algorithms for the Romanian language. Full article
(This article belongs to the Special Issue Curative Power of Medical Data)
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Article
Evolutionary Path of Factors Influencing Life Satisfaction among Chinese Elderly: A Perspective of Data Visualization
1 School of Information Management, Wuhan University, Wuhan 430000, China
2 College of Information, University of North Texas, Denton, TX 76207, USA
Data 2018, 3(3), 35; https://doi.org/10.3390/data3030035 - 11 Sep 2018
Cited by 12 | Viewed by 2170
Abstract
China has the largest aging population of all countries and faces severe aging issues. As an important indicator to measure the quality of life, the life satisfaction of elderly Chinese people has received increasing attention. Based on the cross-sectional survey data collected from [...] Read more.
China has the largest aging population of all countries and faces severe aging issues. As an important indicator to measure the quality of life, the life satisfaction of elderly Chinese people has received increasing attention. Based on the cross-sectional survey data collected from 2002 to 2014, which were provided by the CLHLS (Chinese Longitudinal Healthy Longevity Survey) project as open datasets, this study investigated how the influence and importance of factors associated with life satisfaction in the elderly have changed during these years. In view of previous research and questionnaire data, demographic, physiological, psychological, economic and social characteristics were selected as potential influencing factors of life satisfaction. With the R programming language, we used IV (information value) as the indicator to measure the influence of associated factors and determined the importance of each factor by establishing a random forest model for each year. Data visualization was used to demonstrate change in each factor with the Microsofot PowerPoint 2016. The results show that, for most factors, their influence has fluctuated. Since 2002, the most significant factors have always been self-rated health, self-evaluation of economic level, economic self-sufficiency and bright personality. Full article
(This article belongs to the Special Issue Curative Power of Medical Data)
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