MakeUseOf features five sites for tracking Flu online:
- Google Flu Trends
- The DoD Worldwide Influenza Surveillance Program
- World Health Organization
- Centers for Disease Control
Radiopaedia (previously mentioned here) has made available (at no charge via the iPhone App Store) a Radiopaedia Radiology Teaching File of “50 CNS cases comprising 170 images, questions and detailed text.”
Neat. Still, I’d like to know how many health infomation wikis are set up to deliver a mobile version for a variety of mobile browsers.
This reminds me: I’m going to need to do an update on my list of medical wikis in the near future. If you know of any that I don’t have listed, please leave a comment or drop me an email?
“In addition, because medical knowledge advances at a more rapid pace than the regular print publishing cycles, iPublishCentral gives us the ability to provide more frequent text updates to our most popular books without the added expenses of a new print run.”
For instance, the e-book version of Guides to the Evaluation of Permanent Impairment, sixth edition, contains clarifications and corrections that were not defined until after the book published. The AMA has recently reprinted the book and is using this opportunity to introduce its existing customer base to the electronic version. Direct purchasers can currently receive a two-year subscription to the downloadable e-book as a replacement offer for the reprinted publication. iPublishCentral allows a migration path to a planned suite of e-products that will be available on Impelsys’ iPlatform in the future.
Looking forward to hearing about the e-book strategies of other professional associations.
Some interesting numbers. Not sure about the rest.
This kind of blog is sooooo useful to searchers like me who are clearly less experienced and expert than the author of PubMed Search Strategies, Cindy Schmidt, M.D., M.L.S.
“This blog has been created to share PubMed search strategies. Search strategies posted here are not perfect. They are posted in the hope that others will benefit from the work already put into their creation and/or will offer suggestions for improvements. Librarians who wish to post comments on this blog or who wish to become authors are invited to e-mail me.”
Example post shown below:
[via: Melissa Rethlefsen and Mark Rabnett]
This blog has looked at Clinical Trial search tools previously. Some highlights included:
Also useful for non-clinician is the MedlinePlus page on clinical trials.
Trial-X does a couple of things differently.
First is that it seems Trial-X can gather your demographic information and diagnosis from your Google Health account or your Microsoft HealthVault account and apply it to your clinical trial search.
Second is that the search criteria one can apply is far more detailed than in any of the other search tools I’ve seen.
Then it maps your information on a grid to see if you’re a good match for the trials known to the system:
And if there’s no good match? Trial-X will email you if it finds one.
I’ve only given it a quick once-over, but it looks pretty neat. Anyone else tried it? Any insights?
PubMed-EX is a browser extension that marks up PubMed search results with additional information retrieved from IISR & IASL text-mining services. PubMed-EX’s page mark-up includes section categorization, gene/disease name, and relation.
The mark-ups of PubMed-EX can help researchers quickly focus on key information in retrieved abstracts and can provide additional background information on key terms. Furthermore, our text-mining server carries out all text-mining processing, freeing up users’ resources.
Try this- it’s way cool.
What New Users Should Know
(How is Quertle® different?)
1. Find true relationships, not simple co-occurrences
On Quertle, if you search for two or more terms, you will find documents in which those terms occur in a conceptual relationship, not simply scattered within the same document. You won’t always find as many, but you weren’t really going to read 14,578 documents, were you?
2. Quertle understands biology and chemistry
Quertle understands the difference between “TWIST”, the helix-loop-helix transcription factor, and “twist”, the verb. So, use proper capitalization in your query, and you won’t be lost in a sea of irrelevant results.
3. Power Terms™ enable you to query for categories of objects
Use Power Terms™ to query for categories of objects, such as any protein or chemical (not simply the occurrence of the terms). See the Power Terms™ link under the query box for further instructions and the list of currently-supported Power Terms™. Use them; we’ll know what they mean. Want other Power Terms™? Let us know.
4. Useful help
Throughout the site, mouse over the (?) to see helpful hints. To answer many of your other questions, such as why there appear to be duplicate results, please read the Help and FAQ documents (links at the bottom of the page).
Things to look for on the Results page (check the (?) hints on that page):
a. More relevant results
b. Easy filtering and breadcrumb tracking
c. Key concepts automatically identified for you, including members of any Power Term™ categories used in your query
I definitely like the highlighting of search terms and the terms Quertle sees as synonymous:
I like the refinement tools to the right of search results:
It bothers me a bit that Quertle doesn’t actually identify who created or maintains it:
Who is behind Quertle?
Quertle has been created by biomedical scientists, chemists, and linguistic experts, who have many decades of experience with research and finding relevant information to support that research.
Since Quertle is essentially doing keyword searches, its power would be significantly improved if it supported Boolean operators.
For more, see Quertle’s Help page.
Cyberpsychol Behav. 2009 Aug;12(4):441-4.
More information than you ever wanted: does Facebook bring out the green-eyed monster of jealousy?
Muise A, Christofides E, Desmarais S.
Department of Psychology, University of Guelph, Ontario, Canada. firstname.lastname@example.org
The social network site Facebook is a rapidly expanding phenomenon that is changing the nature of social relationships. Anecdotal evidence, including information described in the popular media, suggests that Facebook may be responsible for creating jealousy and suspicion in romantic relationships. The objectives of the present study were to explore the role of Facebook in the experience of jealousy and to determine if increased Facebook exposure predicts jealousy above and beyond personal and relationship factors. Three hundred eight undergraduate students completed an online survey that assessed demographic and personality factors and explored respondents’ Facebook use. A hierarchical multiple regression analysis, controlling for individual, personality, and relationship factors, revealed that increased Facebook use significantly predicts Facebook-related jealousy. We argue that this effect may be the result of a feedback loop whereby using Facebook exposes people to often ambiguous information about their partner that they may not otherwise have access to and that this new information incites further Facebook use. Our study provides evidence of Facebook’s unique contributions to the experience of jealousy in romantic relationships.
Learned about MedlineRanker through this recent article:
The biomedical literature is represented by millions of abstracts available in the Medline database. These abstracts can be queried with the PubMed interface, which provides a keyword-based Boolean search engine. This approach shows limitations in the retrieval of abstracts related to very specific topics, as it is difficult for a non-expert user to find all of the most relevant keywords related to a biomedical topic. Additionally, when searching for more general topics, the same approach may return hundreds of unranked references. To address these issues, text mining tools have been developed to help scientists focus on relevant abstracts. We have implemented the MedlineRanker webserver, which allows a flexible ranking of Medline for a topic of interest without expert knowledge. Given some abstracts related to a topic, the program deduces automatically the most discriminative words in comparison to a random selection. These words are used to score other abstracts, including those from not yet annotated recent publications, which can be then ranked by relevance. We show that our tool can be highly accurate and that it is able to process millions of abstracts in a practical amount of time. MedlineRanker is free for use and is available at http://cbdm.mdc-berlin.de/tools/medlineranker.