Social health data integration using semantic Web

Chun, Soon Ae; MacKellar, Bonnie

doi:10.1145/2245276.2245351

Cited by 16 publications

(13 citation statements)

References 14 publications

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“…Interviewees from a technical department declared they would never publish health relevant data. This statement is comforting regarding privacy protection but many people already use online forums or social media to seek help for their illnesses [1]. We analyzed the relevant laws in Switzerland.…”

Section: Discussionmentioning

confidence: 99%

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Sensor Data Meets Social Networks Reflecting on Benefits in the Case of a Patient Room

Kuhn

Spichiger

Riedl

2013

Availability, Reliability, and Security in Information Systems and HCI

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Abstract. In a hospital, information exchange is essential to save lives and to prevent life-endangering mistakes. Information exchange is supported by a hospital information system (HIS). From a theoretical perspective, the deployment of an HIS is promising because it reduces errors and duplication of information. In practice, however, there are some major problems concerning the usage of such a system. One way to deal with these problems is introduced in this paper: the integration of sensor data into social media. The paper concentrates on the conceptual benefits and risks such an integration may generate. It focuses on the case of a patient room.

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Section: Discussionmentioning

confidence: 99%

“…This leads to poor recording habits like copy/paste from other reports or shortening notes so they become unspecific. Thus wrong medication 1 and wrong therapy can result.…”

Section: Introductionmentioning

confidence: 99%

Sensor Data Meets Social Networks Reflecting on Benefits in the Case of a Patient Room

Kuhn

Spichiger

Riedl

2013

Availability, Reliability, and Security in Information Systems and HCI

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“…Proprietary CKM tools, as those of Siemens are addressed in Stroetmann and Aisenbrey [1]. A web portal that integrates information from PatientsLikeMe, WebMD, and PubMed is introduced in Chun and MacKellar [11], although such tools, perhaps because of their complexity, are not well accepted by the medical community (Sittig et al [10]). Other tools closer to that proposed in this article are addressed in Rubin et al [12], Bo Hu et al [13] and Möller et al [14].…”

Section: Introductionmentioning

confidence: 99%

A medical knowledge management system based on expert tagging (MKMST)

Baigorri¹,

Villadangos

Astráin

et al. 2013

WIT Transactions on Information and Communication Technologies

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This paper introduces a prototype of a medical knowledge management system (MKMST) for visual expertise in medical diagnostic reasoning and medical education. The system proposed here, developed following medical expert (radiologists) recommendations, is based on medical image tagging and annotation. Medical images stored in picture archiving and communications systems (PACS) are accessed by medical experts to diagnose pathologies by means of a tagging system and the generation of a taxonomy. The system stores the annotations in a relational database management system and interacts via DICOM standard and HL7 with PACS and the health records. The knowledge base consists of the translation from tacit knowledge to explicit knowledge.

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“…All this information centered around the patient answers the query perfectly but is missed by the posted-based search. To improve the recall, we can adopt the thread-based search, which and its variants are also used in many forums, such as the Healthboards message boards 3 and the Epilepsy forum 4 . It returns a thread or its link if all the posts in this thread collectively contain all the queried information.…”

Section: Introductionmentioning

confidence: 99%

“…Related Work: There is some related work on medical information extraction, categorization, or integration on forums or other social media, such as [4,11,12,14]. In [12], statistic machine learning techniques are used to classify the content of each sentence in forum posts into three types: symptom, treatment, or others.…”

Section: Introductionmentioning

confidence: 99%

Patient-centric, multi-role, and multi-dimension information exploration on online healthcare forums

Liu

Chen

2013

Proceedings of the Sixth Workshop on Ph.D. Students in Information and Knowledge Management

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Online healthcare forums provide a valuable platform for people to share medical information and support each other. However, currently the rich information shared on healthcare forums has not been fully explored. In this work, we first motivate the need for patient-centric, multi-role, and multi-dimension information exploration. We then present our patient-centric information exploration prototype system and show its effectiveness with preliminary experiment evaluation. We have also identified some potential techniques for multi-role and multi-dimension information exploration.

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Social health data integration using semantic Web

Cited by 16 publications

References 14 publications

Sensor Data Meets Social Networks Reflecting on Benefits in the Case of a Patient Room

Sensor Data Meets Social Networks Reflecting on Benefits in the Case of a Patient Room

A medical knowledge management system based on expert tagging (MKMST)

Patient-centric, multi-role, and multi-dimension information exploration on online healthcare forums

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