Addendum to Informatics for Health 2017: Advancing both science and practice

This article presents presentation and poster abstracts that were mistakenly omitted from the original publication

Tutorial: Identity Management Systems and Secured Access Control

Identity Management has been a serious problem since the establishment of the Internet. Yet little progress has been made toward an acceptable solution. Early Identity Management Systems (IdMS) were designed to control access to resources and match capabilities with people in well-defined situations, Today’s computing environment involves a variety of user and machine centric forms of digital identities and fuzzy organizational boundaries. With the advent of inter-organizational systems, social networks, e-commerce, m-commerce, service oriented computing, and automated agents, the characteristics of IdMS face a large number of technical and social challenges. The first part of the tutorial describes the history and conceptualization of IdMS, current trends and proposed paradigms, identity lifecycle, implementation challenges and social issues. The second part addresses standards, industry initia-tives, and vendor solutions. We conclude that there is disconnect between the need for a universal, seamless, trans-parent IdMS and current proposed standards and vendor solutions

An integrated database-pipeline system for studying single nucleotide polymorphisms and diseases

<p>Abstract</p> <p>Background</p> <p>Studies on the relationship between disease and genetic variations such as single nucleotide polymorphisms (SNPs) are important. Genetic variations can cause disease by influencing important biological regulation processes. Despite the needs for analyzing SNP and disease correlation, most existing databases provide information only on functional variants at specific locations on the genome, or deal with only a few genes associated with disease. There is no combined resource to widely support gene-, SNP-, and disease-related information, and to capture relationships among such data. Therefore, we developed an integrated database-pipeline system for studying SNPs and diseases.</p> <p>Results</p> <p>To implement the pipeline system for the integrated database, we first unified complicated and redundant disease terms and gene names using the Unified Medical Language System (UMLS) for classification and noun modification, and the HUGO Gene Nomenclature Committee (HGNC) and NCBI gene databases. Next, we collected and integrated representative databases for three categories of information. For genes and proteins, we examined the NCBI mRNA, UniProt, UCSC Table Track and MitoDat databases. For genetic variants we used the dbSNP, JSNP, ALFRED, and HGVbase databases. For disease, we employed OMIM, GAD, and HGMD databases. The database-pipeline system provides a disease thesaurus, including genes and SNPs associated with disease. The search results for these categories are available on the web page <url>http://diseasome.kobic.re.kr/</url>, and a genome browser is also available to highlight findings, as well as to permit the convenient review of potentially deleterious SNPs among genes strongly associated with specific diseases and clinical phenotypes.</p> <p>Conclusion</p> <p>Our system is designed to capture the relationships between SNPs associated with disease and disease-causing genes. The integrated database-pipeline provides a list of candidate genes and SNP markers for evaluation in both epidemiological and molecular biological approaches to diseases-gene association studies. Furthermore, researchers then can decide semi-automatically the data set for association studies while considering the relationships between genetic variation and diseases. The database can also be economical for disease-association studies, as well as to facilitate an understanding of the processes which cause disease. Currently, the database contains 14,674 SNP records and 109,715 gene records associated with human diseases and it is updated at regular intervals.</p

Current Status and Key Issues of Data Management in Tertiary Hospitals: A Case Study of Seoul National University Hospital

Objectives In the era of the Fourth Industrial Revolution, where an ecosystem is being developed to enhance the quality of healthcare services by applying information and communication technologies, systematic and sustainable data management is essential for medical institutions. In this study, we assessed the data management status and emerging concerns of three medical institutions, while also examining future directions for seamless data management. Methods To evaluate the data management status, we examined data types, capacities, infrastructure, backup methods, and related organizations. We also discussed challenges, such as resource and infrastructure issues, problems related to government regulations, and considerations for future data management. Results Hospitals are grappling with the increasing data storage space and a shortage of management personnel due to costs and project termination, which necessitates countermeasures and support. Data management regulations on the destruction or maintenance of medical records are needed, and institutional consideration for secondary utilization such as long-term treatment or research is required. Government-level guidelines for facilitating hospital data sharing and mobile patient services should be developed. Additionally, hospital executives at the organizational level need to make efforts to facilitate the clinical validation of artificial intelligence software. Conclusions This analysis of the current status and emerging issues of data management reveals potential solutions and sets the stage for future organizational and policy directions. If medical big data is systematically managed, accumulated over time, and strategically monetized, it has the potential to create new value

Development of a Mobile Application, “Wild Flowers of Bukhansan National Park (version 1.0)”, for Identification of Plants in Bukhansan National Park

AbstractWe developed the educational purpose mobile application, named “Wild Flowers of Bukhansan National Park (version 1.0)”, aiming for easy identification of wildflowers for students and visitors in the park. When visitors find a flower or part of plant in the park, visitors can search for its name utilizing the pictures and characters provided in their own smartphone mobile devices or tablet PCs. The application provides pictures of wildflowers in the park and character-based searching system based on 12 diagnostic features (e.g., growth form, leaf arrangement, flower symmetry, petal color, petal number, sepal number, etc). We adopted the complete floristic survey of Chung and Lee (1962) and added species that we confirmed their distribution in the park during the development of this application. In summary, number of vascular plants in this park was estimated to be 428 taxa including 100 families, 280 genera, 327 species, 1 subspecies, 50 varieties, and 5 formas. We provided a total of 588 pictures representing 358 taxa and each taxon includes multiple pictures in many cases. Included identification quizzes can be an efficient educational tool as well as fun activity for students and visitors who are learning plant species in Korea. Our next step will include GPS function in the application for indicating visitor's location and for providing previously reported sites of the species that we interested in the map of the park. The future application which includes GPS function will be a valuable tool for the monitoring of rare plants, plant researches related to the climate changes, etc. We currently provide Korean iPhone version only, and English version and both of android versions will be serviced soon

Unravelling data for rapid evidence-based response to COVID-19: a summary of the unCoVer protocol

Introduction unCoVer - Unravelling data for rapid evidence-based response to COVID-19 - is a Horizon 2020-funded network of 29 partners from 18 countries capable of collecting and using real-world data (RWD) derived from the response and provision of care to patients with COVID-19 by health systems across Europe and elsewhere. unCoVer aims to exploit the full potential of this information to rapidly address clinical and epidemiological research questions arising from the evolving pandemic. Methods and analysis From the onset of the COVID-19 pandemic, partners are gathering RWD from electronic health records currently including information from over 22 000 hospitalised patients with COVID-19, and national surveillance and screening data, and registries with over 1 900 000 COVID-19 cases across Europe, with continuous updates. These heterogeneous datasets will be described, harmonised and integrated into a multi-user data repository operated through Opal-DataSHIELD, an interoperable open-source server application. Federated data analyses, without sharing or disclosing any individual-level data, will be performed with the objective to reveal patients' baseline characteristics, biomarkers, determinants of COVID-19 prognosis, safety and effectiveness of treatments, and potential strategies against COVID-19, as well as epidemiological patterns. These analyses will complement evidence from efficacy/safety clinical trials, where vulnerable, more complex/heterogeneous populations and those most at risk of severe COVID-19 are often excluded. Ethics and dissemination After strict ethical considerations, databases will be available through a federated data analysis platform that allows processing of available COVID-19 RWD without disclosing identification information to analysts and limiting output to data aggregates. Dissemination of unCoVer's activities will be related to the access and use of dissimilar RWD, as well as the results generated by the pooled analyses. Dissemination will include training and educational activities, scientific publications and conference communications.info:eu-repo/semantics/publishedVersio