Asynchronous Remote Medical Consultation for Ghana

Computer-mediated communication systems can be used to bridge the gap between doctors in underserved regions with local shortages of medical expertise and medical specialists worldwide. To this end, we describe the design of a prototype remote consultation system intended to provide the social, institutional and infrastructural context for sustained, self-organizing growth of a globally-distributed Ghanaian medical community. The design is grounded in an iterative design process that included two rounds of extended design fieldwork throughout Ghana and draws on three key design principles (social networks as a framework on which to build incentives within a self-organizing network; optional and incremental integration with existing referral mechanisms; and a weakly-connected, distributed architecture that allows for a highly interactive, responsive system despite failures in connectivity). We discuss initial experiences from an ongoing trial deployment in southern Ghana.Comment: 10 page

Deliverable 9 - Evaluation report of training and the use of training tools

Van der Klink, M. R., Kicken, W., Drachsler, H., Stoyanov, S., & Boshuizen, H. P. A. (2011). Deliverable 9 - Evaluation report of training and the use of training tools. Heerlen, The Netherlands, Open Universiteit in the Netherlands.This deliverable describes the design, development and evaluation of a learning network that was developed for medical professionals interested and/or responsible for improving handoversHandover - 2008 - 22340

OPAL Community Environment Report

The Open Air Laboratories network, or OPAL, as it quickly became known, was launched in 2007 following a successful application to the Big Lottery Fund It was the first time that Big Lottery funding on this scale had been awarded to academic institutions. The University of Central Lancashire led by Dr Mark Toogood was responsible for understanding public engagement with OPAL. The Open Air Laboratories (OPAL)network is a nationwide partnership comprising of ten universities and five organisations with grants awarded totalling £14.4 million. • Over half a million people have participated in the OPAL programme. OPAL activities are carried out by people of all ages, backgrounds and abilities, including 10,000 people in ‘hard to reach’ communities. • OPAL opens people’s eyes to the natural world. Nearly half (44%) of OPAL survey participants said that this was the first time that they had carried out a nature survey. 90% of participants have learnt something new. • OPAL has the ability to change people’s behaviour. Almost half (43%) of respondents said OPAL had changed the way they thought about the environment and more than a third (37%) said they will change their behaviour towards it. • In addition to raising environmental awareness, OPAL also improves personal well-being by motivating people to spend time outdoors doing something positive, while connecting with people and nature

A legacy handbook for business support

Legacy Handbook reviewing emda's experience of business support activity. Identifies key achievements and draws out lessons learned that may be relevant to successor bodies active in this area

Understanding and Augmenting Expertise Networks.

This thesis investigates large scale knowledge searching and sharing processes in online communities and organizations. It focuses on understanding the relationship between social networks and expertise sharing activities. The work explores design opportunities of these social networks to bootstrap knowledge sharing, by using the specific social characteristics of social networks which can lead to sizeable differences in the way expertise is searched and shared. The potential impact of this approach was examined in three related studies using data from Java Forum, Yahoo Answers, and Enron. The Java Forum study investigated how people asked and answered questions in this online community using advanced social network analysis metrics. Furthermore, it explored algorithms that made use of the network structure to evaluate expertise levels. It also used simulations to explore possible social structures and dynamics that would affect the interaction patterns and network structure in online communities. The Yahoo Answers study extended the Java Forum study into a more general community setting and covered much more diverse knowledge sharing dynamics. It analyzed both content properties and social network interactions across sub-forums with different types of knowledge, as well as examined the range and depth of knowledge that users share across these sub-forums. The Enron study, on the other hand, investigated how social network structure could affect the expertise searching process in organizational communication networks using simulations and social network analysis. Based on findings in these studies, a novel expertise sharing system, QuME, was proposed and developed. This thesis provides a network theoretical foundation for the analysis and design of knowledge sharing communities. It explores new opportunities and challenges that arise in online social interaction environments, which are becoming increasingly ubiquitous and important. This work also has direct implications for practitioners. The ability to add the level of expertise would be a major step forward for expertise finding systems, and would likely open up a range of new application possibilities.Ph.D.InformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/58450/1/junzh_1.pd

Conceptual graph-based knowledge representation for supporting reasoning in African traditional medicine

Although African patients use both conventional or modern and traditional healthcare simultaneously, it has been proven that 80% of people rely on African traditional medicine (ATM). ATM includes medical activities stemming from practices, customs and traditions which were integral to the distinctive African cultures. It is based mainly on the oral transfer of knowledge, with the risk of losing critical knowledge. Moreover, practices differ according to the regions and the availability of medicinal plants. Therefore, it is necessary to compile tacit, disseminated and complex knowledge from various Tradi-Practitioners (TP) in order to determine interesting patterns for treating a given disease. Knowledge engineering methods for traditional medicine are useful to model suitably complex information needs, formalize knowledge of domain experts and highlight the effective practices for their integration to conventional medicine. The work described in this paper presents an approach which addresses two issues. First it aims at proposing a formal representation model of ATM knowledge and practices to facilitate their sharing and reusing. Then, it aims at providing a visual reasoning mechanism for selecting best available procedures and medicinal plants to treat diseases. The approach is based on the use of the Delphi method for capturing knowledge from various experts which necessitate reaching a consensus. Conceptual graph formalism is used to model ATM knowledge with visual reasoning capabilities and processes. The nested conceptual graphs are used to visually express the semantic meaning of Computational Tree Logic (CTL) constructs that are useful for formal specification of temporal properties of ATM domain knowledge. Our approach presents the advantage of mitigating knowledge loss with conceptual development assistance to improve the quality of ATM care (medical diagnosis and therapeutics), but also patient safety (drug monitoring)

User's Privacy in Recommendation Systems Applying Online Social Network Data, A Survey and Taxonomy

Recommender systems have become an integral part of many social networks and extract knowledge from a user's personal and sensitive data both explicitly, with the user's knowledge, and implicitly. This trend has created major privacy concerns as users are mostly unaware of what data and how much data is being used and how securely it is used. In this context, several works have been done to address privacy concerns for usage in online social network data and by recommender systems. This paper surveys the main privacy concerns, measurements and privacy-preserving techniques used in large-scale online social networks and recommender systems. It is based on historical works on security, privacy-preserving, statistical modeling, and datasets to provide an overview of the technical difficulties and problems associated with privacy preserving in online social networks.Comment: 26 pages, IET book chapter on big data recommender system