Supporting Collaboration of Medical Informatics Researchers and Teams

Podgorelec, Vili; Pavlič, Luka

doi:10.1109/cbms.2007.102

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…Semantic Web technologies have been put forward as enablers of Internet-based tools supporting knowledge-intensive tasks [ 15 , 17 ]. A key component of the Semantic Web is the representation of knowledge in a computer-processable manner, in the form of ontologies [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

SOMWeb: A Semantic Web-Based System for Supporting Collaboration of Distributed Medical Communities of Practice

Falkman¹,

Gustafsson²,

Jontell³

et al. 2008

J Med Internet Res

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Background Information technology (IT) support for remote collaboration of geographically distributed communities of practice (CoP) in health care must deal with a number of sociotechnical aspects of communication within the community. In the mid-1990s, participants of the Swedish Oral Medicine Network (SOMNet) began discussing patient cases in telephone conferences. The cases were distributed prior to the conferences using PowerPoint and email. For the technical support of online CoP, Semantic Web technologies can potentially fulfill needs of knowledge reuse, data exchange, and reasoning based on ontologies. However, more research is needed on the use of Semantic Web technologies in practice.Objectives The objectives of this research were to (1) study the communication of distributed health care professionals in oral medicine; (2) apply Semantic Web technologies to describe community data and oral medicine knowledge; (3) develop an online CoP, Swedish Oral Medicine Web (SOMWeb), centered on user-contributed case descriptions and meetings; and (4) evaluate SOMWeb and study how work practices change with IT support.Methods Based on Java, and using the Web Ontology Language and Resource Description Framework for handling community data and oral medicine knowledge, SOMWeb was developed using a user-centered and iterative approach. For studying the work practices and evaluating the system, a mixed-method approach of interviews, observations, and a questionnaire was used.Results By May 2008, there were 90 registered users of SOMWeb, 93 cases had been added, and 18 meetings had utilized the system. The introduction of SOMWeb has improved the structure of meetings and their discussions, and a tenfold increase in the number of participants has been observed. Users submit cases to seek advice on diagnosis or treatment, to show an unusual case, or to create discussion. Identified barriers to submitting cases are lack of time, concern about whether the case is interesting enough, and showing gaps in one’s own knowledge. Three levels of member participation are discernable: a core group that contributes most cases and most meeting feedback; an active group that participates often but only sometimes contribute cases and feedback; and a large peripheral group that seldom or never contribute cases or feedback.Conclusions SOMWeb is beneficial for individual clinicians as well as for the SOMNet community. The system provides an opportunity for its members to share both high quality clinical practice knowledge and external evidence related to complex oral medicine cases. The foundation in Semantic Web technologies enables formalization and structuring of case data that can be used for further reasoning and research. Main success factors are the long history of collaboration between different disciplines, the user-centered development approach, the existence of a “champion” within the field, and nontechnical community aspects already being in place.

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Section: Introductionmentioning

confidence: 99%

SOMWeb: A Semantic Web-Based System for Supporting Collaboration of Distributed Medical Communities of Practice

Falkman¹,

Gustafsson²,

Jontell³

et al. 2008

J Med Internet Res

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“…In medicine, remote collaboration applications provide vast benefits to both healthcare providers and their patients. One of the most significant advantages is that it enables radiologists and referring clinicians to communicate [22,33,48] in various ways, for instance through instant messaging, or VoiP using a microphone or headset. The most obvious need for remote collaboration is the reduction in travel cost and time required in attending meetings to discuss a patient's condition [11,33,36].…”

Section: The Need For Collaboration In Radiology Reportingmentioning

confidence: 99%

MaRRS : a software system for generating multimedia radiology reports using Adobe Acrobat

Moniz¹

2021

Preprint

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Despite the proliferation of multimedia software technologies, radiology reports continue to lack image content that would improve the ability of referring clinicians to fully interpret and analyze radiological findings. This thesis demonstrates that it is possible to construct a radiology reporting software system that contains both text and image content using only "off-the-shelf" multimedia software. Specifically, a software system is presented that provides enhanced visual multimedia capabilities, structured content, and reduced report production time, using a well-known PDF program, Adobe Acrobat. The system, which we call the Multimedia Radiology Report System, or MaRRs, allows radiologists to quickly and simply create and deliver effective interactive multimedia medical reports. A detailed analysis describing the unique structure and functionality of MaRRS will be presented to demonstrate its advantages for both radiologists and referring clinicians.

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“…European Patient Summary ( 153 ) is one such project whose backbone lies in the semantic web technologies. Besides this, ontologies and semantics have also been used by Podgorelec and Pavlic ( 139 ) to store and integrate the data about Mitral Valve Proplapse syndrome. Kim and Choi ( 140 ) presented an electrocardiography ontology for heart diseases and used it to create a knowledge base.…”

Section: Industrial Applications Of Ontology Learningmentioning

confidence: 99%

A survey of ontology learning techniques and applications

et al. 2018

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Ontologies have gained a lot of popularity and recognition in the semantic web because of their extensive use in Internet-based applications. Ontologies are often considered a fine source of semantics and interoperability in all artificially smart systems. Exponential increase in unstructured data on the web has made automated acquisition of ontology from unstructured text a most prominent research area. Several methodologies exploiting numerous techniques of various fields (machine learning, text mining, knowledge representation and reasoning, information retrieval and natural language processing) are being proposed to bring some level of automation in the process of ontology acquisition from unstructured text. This paper describes the process of ontology learning and further classification of ontology learning techniques into three classes (linguistics, statistical and logical) and discusses many algorithms under each category. This paper also explores ontology evaluation techniques by highlighting their pros and cons. Moreover, it describes the scope and use of ontology learning in several industries. Finally, the paper discusses challenges of ontology learning along with their corresponding future directions.

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Supporting Collaboration of Medical Informatics Researchers and Teams

Cited by 3 publications

References 8 publications

SOMWeb: A Semantic Web-Based System for Supporting Collaboration of Distributed Medical Communities of Practice

SOMWeb: A Semantic Web-Based System for Supporting Collaboration of Distributed Medical Communities of Practice

MaRRS : a software system for generating multimedia radiology reports using Adobe Acrobat

A survey of ontology learning techniques and applications

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