Today, healthcare has become one of the largest and most fast-paced industries due to the rapid development of digital healthcare technologies. The fundamental thing to enhance healthcare services is communicating and linking massive volumes of available healthcare data. However, the key challenge in reaching this ambitious goal is letting the information exchange across heterogeneous sources and methods as well as establishing efficient tools and techniques. Semantic Web (SW) technology can help to tackle these problems. They can enhance knowledge exchange, information management, data interoperability, and decision support in healthcare systems. They can also be utilized to create various e-healthcare systems that aid medical practitioners in making decisions and provide patients with crucial medical information and automated hospital services. This systematic literature review (SLR) on SW in healthcare systems aims to assess and critique previous findings while adhering to appropriate research procedures. We looked at 65 papers and came up with five themes: e-service, disease, information management, frontier technology, and regulatory conditions. In each thematic research area, we presented the contributions of previous literature. We emphasized the topic by responding to five specific research questions. We have finished the SLR study by identifying research gaps and establishing future research goals that will help to minimize the difficulty of adopting SW in healthcare systems and provide new approaches for SW-based medical systems' progress.

https://downloads.hindawi.com/journals/ijclp/2022/6807484.pdf

Semantic Web in Healthcare: A Systematic Literature Review of Application, Research Gap, and Future Research Avenues

Currently, efforts have focused on dealing with the emerging coronavirus disease 2019 (COVID-19) worldwide Hopefully, information technology can be applied to meet the challenges related to the pandemic and biosurveillance Free and open-source software (FOSS) model has emerged as an effective tool against these challenges The main objective of this study was to determine and summarize the application of FOSS in published and released resources and materials against COVID-19 This review includes projects that were available through GitHub and SourceForge reliable web-based materials All projects were identified between January 1 and April 10, 2020 Search terms in GitHub and Source Forge were based on clinical terminologies, such as COVID-19, COVID, Covid19, and Corona Virus Inclusion or exclusion criteria were used to filter the results Finally, a screening procedure was followed to achieve the most related records We identified 46,426 records in GitHub and seven projects in Source Forge The top 40 projects were included The results show that a high percentage of FOSS projects against COVID-19 were related to visual dashboards The open dataset and analytical methods made a significant contribution to this context Previously learned lessons from FOSS have shown that the explained projects would play important roles in future epidemics by forking and joining in new projects, which formed around a specific problem

/pdf/information-technology-efforts-against-covid-19-a-review-of-55z0glft9d.pdf

Information technology efforts against COVID-19: A review of open source projects

AbstractGenerally, skin diseases are taken seriously only after it gets aggravated. Many patients do not feel comfortable to consult physician for their skin problems and try to cure with home remedies. Identifying good dermatologist is more challenging. Disease gets cured with ease, if treated properly otherwise it becomes complicated. To handle this, knowledge-based decision support system is developed which provide recommendation for treatment. System realizes patient’s symptoms with location, cause and recommends appropriate medicines. Ontology is used to elaborate data concepts and their relationships in skin disease, which permits sharing and reuse of domain knowledge. Semantics described using Web Ontology Language (OWL) with vocabularies, resources, logic’s, and inference rules are queried for relevant information through SPARQL. System proved to render most valuable service to skin patients with ease and accuracy of its recommendation is high. It renders best treatment in COVID situation where people’s movement is restricted to great extent.KeywordsKnowledge informationSemantic webOntologyRule-based systemInference rulesMedicine recommendation 

Rule Based Medicine Recommendation for Skin Diseases Using Ontology with Semantic Information

Web service composition is a novel methodology to integrate diverse business solutions to accomplish complex business logic. In this fast-paced digital era with diverse categories of users, intelligent service composition based on the contextual information is highly essential to satisfy individual users requirements. For intelligent composition, ontology based declarative knowledge model is used to describe the business rules, commercial directions and personalized user environment in machine comprehensible way. This paper depicts healthcare service composition with domain ontology to encompass ontology manipulation, contextual information gathering, selecting services and dynamic composition. E-healthcare system automates service composition which invokes hospital, ambulance, scan-laboratory and pharmacy services. It provide valuable information like nearest hospital, best ambulance, scan-laboratory facilities, appropriate department and doctor details by gathering the contextual inforamtion of users like location, severity, symptoms, etc. Thus, elaborare search process is eliminated which ultimately helps the user to save time and life in case of emergency situations. thod.

Aparna Krishnan

Papers

Contextual Aware Dynamic Healthcare Service Composition Based on Semantic Web Ontology