Ch. Elsner, D. Häckl, H. van der Slikke, V. Della Mea, T.N. Arvanitis, H. Wiesmeth
<span title="2007-09-18">2007</span> <i title="IOS Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/fonjxw6ldrfrvmlrvautcihwwm" style="color: black;">Technology and Health Care</a> </i> &nbsp;
Does the world really need another search engine? This work will give a clear answer. Search engines allow full text search for words but they all fail miserably when it comes to more complex topics like bio-medical research. Today's search technology is in early infant stage and a lot of important information remains buried in the masses of text [1]. Objective: To give insight in the work with the Transinsight Search Engine and quantify the huge potential in terms of Business Value for
more &raquo; ... Methods: Classical searches are successful in helping users to find pointers to information based keywords such as a telephone number on a web page. But they are not successful answering complex questions. We call the process of answering complex questions, which is predominant in the life sciences, knowledge searches. Transinsight's search technologies add a new dimension to traditional search by automatically merging information from documents with knowledge networks. GoPubMed is able to retrieve PubMed abstracts for your search query. Using novel award winning text mining methods for automated recognition of concepts, GoPubMed detects terms from the Gene Ontology (GO) and Medical Subject Headings (MeSH) in the abstracts, displays the subset of the GO and MeSH relevant to the keywords, and allows you to browse the ontologies and display only papers containing specific GO and MeSH terms. Now the GO and MeSH hierarchies can be used to systematically explore the search results. GO and MeSH serve as table of contents in order to structure the over 16 million articles of the MEDLINE data base. Transinsight's core technology is to matching huge amounts of text to huge knowledge-networks fully automated. We deal with 16 Million documents and 120,000 ontology terms. Results: Transinsight developed GoPubMed, a biomedical search engine which uses background knowledge for searches and leads faster to much better search results. Field tests showed, that estimated time savings for knowledge searches are at least 50%: In the life sciences approx. 600,000 scientists are employed. In average they spend 12.4 hours per week searching for relevant Information. Using the technology consequently would help to rise the effectiveness at about 10-15%. Conclusion: The key for enabling search machines to communicate with the searchers is the usage of knowledge. The Transinsight approach is highly suitable to leverage the high potential that lies in faster and more efficient search in lifescience specially for scientific purposes. The shown effect over time savings can help scientists to concentrate on research rather than searching. Additional to this high potential of searching 50% faster, Transinsights Technology can also be targeted at the common market for text related software and services, which is growing rapidly. In mid-2006 "data and text mining is an expanding field and constitutes a market estimated to be more than US$12 billion." [2]. Today Transinsight's search technology is tailored for the life sciences. * These authors were submitted as lecturers of the presentation. 0928-7329/07/$17.00  2007 -IOS Press and the authors. All rights reserved www.imedo.de -A healthcare virtual community Background: imedo.de is an online health community which was launched on April 1 st , 2007, focusing on peer-to-peer interaction between patients. The community is providing a set of diverse features which are focused on empowering individuals to connect and share health-experiences. Main features are as follows: 1) create and administer local support groups through group functionality 2) find out about treatments which helped for certain conditions (use wisdom / experience of the crowd to find top treatments) 3) set personal health goals and receive motivation from so-called "motivators" 4) ask health-related questions 5) write a health-journal and tell other's about your current conditions / feelings 6) every user has a comprehensive online health profile where he enters his health interests -other users can connect to this user via profile information. In addition to that, all data is geo-tagged, which enables users to find e.g. diabetics in the same region -this in turn empowers to connect and share experiences. Many innovative features and tools like SMS-Medication-Intake-Reminders / Doctor's appointment reminders are provided and tested in order to see if these simple yet potentially powerful tools help to improve patient's recovery / treatment / well-being in general. Objective: This work is intented to share insights into how users work with provided tools and how interaction helps them to reach their health goals. Moreover, the question of privacy issues in online health communities will be discussed. This issue is very critical since information on the indivual's health status can influence diverse decisions, for example on the labour market. Methods: The work is divided into two parts: one deals with the privacy issues and thus shows criteria a healthcare virtual community has to meet while the other part concentrates more on the user's behaviour. Therefore, anonymized REAL usage statistics of www.imedo.de will be used as data source for the presentation. Furthermore panel data of imedo.de users will be presented. Results: Data will reveal that users increasingly interact with each other to discuss health issues. Conclusion: Virtual communities will become more and more common in future. The internet is used as a tool for communication between individuals. Long-term data will have to be collected to give more insights in how people use the internet to deal with their personal health challenges.
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