ترغب بنشر مسار تعليمي؟ اضغط هنا

Digital personal health libraries: a systematic literature review

108   0   0.0 ( 0 )
 نشر من قبل Chi Zhang
 تاريخ النشر 2020
  مجال البحث الهندسة المعلوماتية
والبحث باللغة English




اسأل ChatGPT حول البحث

Objective: This paper gives context on recent literature regarding the development of digital personal health libraries (PHL) and provides insights into the potential application of consumer health informatics in diverse clinical specialties. Materials and Methods: A systematic literature review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Here, 2,850 records were retrieved from PubMed and EMBASE in March 2020 using search terms: personal, health, and library. Information related to the health topic, target population, study purpose, library function, data source, data science method, evaluation measure, and status were extracted from each eligible study. In addition, knowledge discovery methods, including co-occurrence analysis and multiple correspondence analysis, were used to explore research trends of PHL. Results: After screening, this systematic review focused on a dozen articles related to PHL. These encompassed health topics such as infectious diseases, congestive heart failure, electronic prescribing. Data science methods included relational database, information retrieval technology, ontology construction technology. Evaluation measures were heterogeneous regarding PHL functions and settings. At the time of writing, only one of the PHLs described in these articles is available for the public while the others are either prototypes or in the pilot stage. Discussion: Although PHL researches have used different methods to address problems in diverse health domains, there is a lack of an effective PHL to meet the needs of older adults. Conclusion: The development of PHLs may create an unprecedented opportunity for promoting the health of older consumers by providing diverse health information.



قيم البحث

اقرأ أيضاً

Wearable devices generate different types of physiological data about the individuals. These data can provide valuable insights for medical researchers and clinicians that cannot be availed through traditional measures. Researchers have historically relied on survey responses or observed behavior. Interestingly, physiological data can provide a richer amount of user cognition than that obtained from any other sources, including the user himself. Therefore, the inexpensive consumer-grade wearable devices have become a point of interest for the health researchers. In addition, they are also used in continuous remote health monitoring and sometimes by the insurance companies. However, the biggest concern for such kind of use cases is the privacy of the individuals. There are a few privacy mechanisms, such as abstraction and k-anonymity, are widely used in information systems. Recently, Differential Privacy (DP) has emerged as a proficient technique to publish privacy sensitive data, including data from wearable devices. In this paper, we have conducted a Systematic Literature Review (SLR) to identify, select and critically appraise researches in DP as well as to understand different techniques and exiting use of DP in wearable data publishing. Based on our study we have identified the limitations of proposed solutions and provided future directions.
102 - Yue Liu , Qinghua Lu , Liming Zhu 2021
Blockchain has been increasingly used as a software component to enable decentralisation in software architecture for a variety of applications. Blockchain governance has received considerable attention to ensure the safe and appropriate use and evol ution of blockchain, especially after the Ethereum DAO attack in 2016. To understand the state-of-the-art of blockchain governance and provide an actionable guidance for academia and practitioners, in this paper, we conduct a systematic literature review, identifying 34 primary studies. Our study comprehensively investigates blockchain governance via 5W1H questions. The study results reveal several major findings: 1) the adaptation and upgrade of blockchain are the primary purposes of blockchain governance, while both software quality attributes and human value attributes need to be increasingly considered; 2) blockchain governance mainly relies on the project team, node operators, and users of a blockchain platform; and 3) existing governance solutions can be classified into process mechanisms and product mechanisms, which mainly focus on the operation phase over the blockchain platform layer.
Knowledge graphs represent concepts (e.g., people, places, events) and their semantic relationships. As a data structure, they underpin a digital information system, support users in resource discovery and retrieval, and are useful for navigation and visualization purposes. Within the libaries and humanities domain, knowledge graphs are typically rooted in knowledge organization systems, which have a century-old tradition and have undergone their digital transformation with the advent of the Web and Linked Data. Being exposed to the Web, metadata and concept definitions are now forming an interconnected and decentralized global knowledge network that can be curated and enriched by community-driven editorial processes. In the future, knowledge graphs could be vehicles for formalizing and connecting findings and insights derived from the analysis of possibly large-scale corpora in the libraries and digital humanities domain.
Scientists always look for the most accurate and relevant answers to their queries in the literature. Traditional scholarly digital libraries list documents in search results, and therefore are unable to provide precise answers to search queries. In other words, search in digital libraries is metadata search and, if available, full-text search. We present a methodology for improving a faceted search system on structured content by leveraging a federation of scholarly knowledge graphs. We implemented the methodology on top of a scholarly knowledge graph. This search system can leverage content from third-party knowledge graphs to improve the exploration of scholarly content. A novelty of our approach is that we use dynamic facets on diverse data types, meaning that facets can change according to the user query. The user can also adjust the granularity of dynamic facets. An additional novelty is that we leverage third-party knowledge graphs to improve exploring scholarly knowledge.
Context:Software Development Analytics is a research area concerned with providing insights to improve product deliveries and processes. Many types of studies, data sources and mining methods have been used for that purpose. Objective:This systematic literature review aims at providing an aggregate view of the relevant studies on Software Development Analytics in the past decade (2010-2019), with an emphasis on its application in practical settings. Method:Definition and execution of a search string upon several digital libraries, followed by a quality assessment criteria to identify the most relevant papers. On those, we extracted a set of characteristics (study type, data source, study perspective, development life-cycle activities covered, stakeholders, mining methods, and analytics scope) and classified their impact against a taxonomy. Results:Source code repositories, experimental case studies, and developers are the most common data sources, study types, and stakeholders, respectively. Product and project managers are also often present, but less than expected. Mining methods are evolving rapidly and that is reflected in the long list identified. Descriptive statistics are the most usual method followed by correlation analysis. Being software development an important process in every organization, it was unexpected to find that process mining was present in only one study. Most contributions to the software development life cycle were given in the quality dimension. Time management and costs control were lightly debated. The analysis of security aspects suggests it is an increasing topic of concern for practitioners. Risk management contributions are scarce. Conclusions:There is a wide improvement margin for software development analytics in practice. For instance, mining and analyzing the activities performed by software developers in their actual workbench, the IDE.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا