…should have one of these.
This nifty tool from the University of Michigan Comprehensive Cancer Center makes it extra easy to search PubMed for articles by authors affiliated with the institution.
…should have one of these.
This nifty tool from the University of Michigan Comprehensive Cancer Center makes it extra easy to search PubMed for articles by authors affiliated with the institution.
I think it was a little over a year ago that I gave up on the idea of building my own portal for medical information RSS feeds because I had started chatting with Frankie Dolan (of MedWorm and LibWorm fame) and suggesting ideas to her instead. I still get most of my medical RSS feeds from MedWorm, but I’m enjoying seeing how others are building medical RSS portals.
I learned that UW-M libraries were up to good RSS-ish things from Ratcatcher’s post the other day that contained an abstract of an upcoming paper:
Developing and Marketing an RSS Journal Service for your Library
Authors: Erika L. Sevetson, MS, Christopher Hooper-Lane, MA, AHIP, Allan R. Barclay, MLIS, AHIP, Ebling Library, University of Wisconsin – Madison; Deborah Copperud, MA, School of Library and Information Science, University of Wisconsin – Madison
Abstract: More and more journals are making their tables of contents available via RSS feed; however, barriers still exist between the user and the content. A working group at a large, Midwestern academic health sciences library set out in Fall 2006 to “explore possibilities for developing an RSS current awareness service that would categorize health sciences RSS feeds and integrate them with SFX, document delivery, and RefWorks.” We developed a 4-phase plan, including overhauling our existing RSS journal feeds pages, developing bundled OPML packages for quick subscription to several journals, developing a shopping cart-like application for users to easily create customized collections, and developing instructional and promotional plans for staff and patrons. This panel will provide an overview of the project, focusing on work process, technology, marketing, and instruction and education. The panel discussion will include 15 minutes for audience discussion.
(Since I won’t be able to make it to this event, could someone please send me lots of detailed notes? Transcripts? Video recordings? Holograms?)
A little digging turned up this page at Ebling which lets the user select a subject, then see available RSS feeds for journals covering that subject (without reloading the page- a nice AJAXy touch). For example: Say we’ve got a hypothetical cardiologist: she could click “Cardiology” and get a nice list of TOC feeds for journals (through EZproxy) of interest to cardiologists.
Since the feed is retrieved through EZproxy, I’m guessing that these feeds will allow the user to click on an item in an aggregator and log in through EZproxy to get the full text. I also like that it offers an OPML file for ALL the feeds in the subject. Awesome. (Next, maybe they could add filtering functions to let our example hypothetical cardiologist user filter the journal feeds she selects for keywords she cares most about.)
The Harvey Semester JournalBot takes a sort of a “wizard” approach, guiding our hypothetical cardiologist through a process of creating a personalized feed (via PubMed API?) tailored for her specific needs and preferences.
First, the JournalBot asks the user to select a subject from a drop-down menu:
(The JournalBot can also let the user enter a MeSH term, but if the user had mastery of MeSH, she wouldn’t need the “wizard.”)
Next the JournalBot prompts the user to select a specific cardiovascular disorder:
Now JournalBot prompts the user to select from which journals she wants articles on this specific cardiovascular disorder…
…and asks the user to choose how many articles from each journal she wants and how old the articles can be:
Lastly, JournalBot offers the user a vanilla feed and a link to add the feed to Google Reader or iGoogle:
I love to see that academic medical libraries are developing services like these, and can’t wait to see what else is coming.
I finished writing this post last night, but hadn’t posted it yet. Since Berci has beat me to it, I’ll go ahead and post it now.
Curehunter.com has a “visual medical dictionary” that I’m having lots of fun playing with, even though I’m not sure that it is best described as a “dictionary.”
Really, it’s a nifty third-party PubMed/MEDLNE tool to visually browse MeSH (as an alternative to the NLM’s MeSH browser). As shown in the screen capture below, it gives the MeSH scope note for “colitis, ulcereative” as the definition for “ulcerative colitis.”
Then it grabs related terms from the MeSH Tree Structures and counts the number of citation hits for each:
Lastly, it gives you a visual, color-coded representation of related strongly related terms from the literature…
…and it does this all in three side-by-side frames:
You really should click over and check it out. The design is deceptively simple, lovely and easy to use.
There’s not enough room for everything, so here are the highlights:
Hot Topics option:
Displays visual representations of how many articles with your concept have been published, top authors and journals, and provides a graphic of countries in which the research is being done. Notably, a disclaimer is posted that states quantity is not the same as quality.
Lists citations clearly, beautifully. Your search term (and impressively, the main topics of the article) are unobtrusively but obviously highlighted. The icons are clear and easy to use, including an option that lets you toggle between citation and abstract view for each listing. Also gives one click options for related genes, which is great, but I’m less (read: Not) pleased with the one click option for wikipedia entries.
What I like best is that on the left hand side, both GO and MeSH relevant terms are listed first in top popularity, then in hierarchy of content, and you can click on a term to refine your search. PubMed, take note!
Gives the ability to search in full text, anywhere, abstract or title, title, author or affiliation (and a few others), allowing for a lot of flexibility and focus. The simplicity of this page puts Google’s Scholar advanced search to shame.
Depending on the researcher and their topic, this is one of the few free third party tools I’d recommend.
I was going to review Twease today, but I realized that David already did a great job with it, and that one of its creators, Fabien Campagne, left additional notes in the comments section that make for a complete review of what it does and how it works.
What neither of them touched on, though, was how beautifully designed it is. Go take a look. Meant as a compliment, I’d call it the “targetization” of Medline!
Also, I think it has one of the most straight forward, easy to use and understand tutorials I’ve seen.
And while I’m on tutorials I’d recommend, check out this Ovid Medline one from Duke.
Earlier I was thinking about which third-party PubMed tool to review, when I noticed that something didn’t seem right. Then it hit me: I’m not being specific. I’ve been using the terms PubMed and Medline interchangeably, when that is incorrect.
MEDLINE is the largest component of PubMed…snip…In addition to MEDLINE citations, PubMed also contains:
In-process citations which provide a record for an article before it is indexed with MeSH and added to MEDLINE or converted to out-of-scope status.
Citations that precede the date that a journal was selected for MEDLINE indexing (when supplied electronically by the publisher).
Some OLDMEDLINE citations that have not yet been updated with current vocabulary and converted to MEDLINE status.
Citations to articles that are out-of-scope (e.g., covering plate tectonics or astrophysics) from certain MEDLINE journals, primarily general science and general chemistry journals, for which the life sciences articles are indexed with MeSH for MEDLINE.
Some life science journals that submit full text to PubMedCentral® and may not yet have been recommended for inclusion in MEDLINE although they have undergone a review by NLM, and some physics journals that were part of a prototype PubMed in the early to mid-1990’s.
I’ve been saying PubMed third party tools, when what I *so far* have meant is third party tools for Medline.
So, today I tried out Medie. I’d said I’d write about it as a third party Medline tool. I can’t. At least not as a hospital librarian. I was going to try to give it a pat on its back and insincerely flash it half a smile so it wouldn’t feel too badly about itself.
Instead, I’ll tell you what I really think of it. The first problem I noticed was that it doesn’t use MeSH (and therefore you can’t focus or use subheadings), so you’re losing massive precision right away. The other biggie I couldn’t get past was that it lists by PMID number, not title and author.
Sounds like I hate it, right? Not at all. Once I learned more about it and understood what it does, I was blown away.
This has changed my mind completely.
Let me take a step back for a moment. One of the first things I mention when I teach Medline is that you are using a computer. You can’t talk to it like you are asking me a question. You need to represent your concepts with words and terms and phrases and connect them appropriately. Then I launch into Boolean logic and MeSH.
Medie is a project of Tsujii Laboratory at the University of Tokyo that works on Natural Language Processing and Computational Linguistics. Basically, this means that it can root your word and process algorithms so that you search the database with natural language. If it doesn’t already, it will be “thinking” that when you type heart you may also like results with cardiac. That is too basic of an example, but hopefully you get the idea.
So, when you search Medie you enter search terms into basic parts of speech (subject, verb, object) and out pop your results, with the line or two of text it picked up color-coded by part of speech. It does have some additional search options that I can see as being very useful and helpful. But as I can’t recommend it for searching now, I’ll let you discover those on your own. I should note that I didn’t find any information on what text is searched or omitted, or how results are ranked.
But in the future I can see Hal saying: “I’m sorry, Dave I’m afraid I can do that.”
Provided by the Dartmouth Biomedical Libraries, Dartmouth College and the Cushing/Whitney Medical Library, Yale School of Medicine, the EBM Page Generator looks like a wonderful tool to help a medical library create an EBM page on its intranet, even without extensive Web development skills.
Welcome to the EBM Page Generator!
Let us help you create your own EBM web page with your resources for your website. Once you’ve gone through the process, you’ll end up with the code to export to your own web site.
In five simple steps, your library can select the resources it has available and wishes to include, plug in the appropriate URLs, then copy and paste the code it generates into the appropriate intranet page.
This is a great idea, implemented very nicely.
Hat tip: Ratcatcher’s del.icio.us favorites
..web-based tool to search Medline at the abstract level (available from http://twease.org). Twease indexes each word of Medline and provides features that can transparently expand your search to help find the information you are looking for.
Twease searches are also partially case sensitive. Short terms are case sensitive, while longer terms are not. For instance, TnT is different from TNT (TnT often stands for Troponin T while TNT often stands for trinitrotoluene). For more details on Twease’s case sensitivity, see the Case Sensitive Searches tutorial page.
Finally, Twease can automatically discover common abbreviations for search phrases (e.g., “protein kinase C” will discover PKC, PK-C, aPKC, etc.) and rewrite queries to use these abbreviations. This feature is available through the Slider (on the top right) and the Advanced pane.
I like the way you can save an individual references to a list that can be exported to BibTeX or EndNote.
Still, I’m not entirely clear on when Twease would actually be preferable to PubMed’s native interface. Would I pretty much save it for when I need to write a query that uses abbreviations or case-sensitive terms?
The Twease project home page includes sources, binary and other information.
The more I play with pmid.us, the more I like it.
Say you want to post a link to the PubMed abstract for PMID: 12472752. The appropriate gigantic URL would be:
If we want to fetch two abstracts, we can do that by adding a “+” and the second PMID:
(http://pmid.us/[First PMID]+[Second PMID])
We can even retrieve three abstracts this way:
(http://pmid.us/[First PMID]+[Second PMID]+[ThirdPMID])
Or we can fetch articles related to PMID 17146093:
You can even run a (simple) search with pmid.us:
(http://pmid.us/[First search term]+[Second search term])
But these aren’t even the coolest thing about pmid.us. The coolest thing about pmid.us is the batch search, which runs multiple searches simultaneously so the user can compare counts of hits. The default demonstration search is a great illustration, but I thought I’d try one of my own.
In the Search for: field, I enter:
colitis OR “ulcerative colitis” OR crohns OR crohn’s OR “crohns disease” OR “crohn’s disease” OR “inflammatory bowel disease” OR IBD
In the AND with: field, I enter:
probiotics OR prebiotics
probiotics AND prebiotics
pmid.us runs these four searches, gives me a link to each set of results, and will count the number of hits in each.
There’s no indication on the site of who created pmid.us and and why (although the domain appears to be registered by Terry Bird of Palatine, IL). I just want to know to whom my thank-you card should be sent.
eTBLAST: a web server to identify expert reviewers, appropriate journals and similar publications.
Nucleic Acids Res. 2007 Apr 22
Errami M, Wren JD, Hicks JM, Garner HR.
Free full text:
If you’re visiting this post from UIUC, would you be so kind as to leave a comment or drop me an email to let me in what context the post was linked to? Thanks!
MEDgle has been getting a lot of attention lately (Dean Giustini brought it up in a post to Medlib-L yesterday while the post you’re reading now was only half-finished), but it’s model isn’t really new. There are actually a good handful of tools with which one can search by symptom. There are of course questions of efficacy and accuracy- and I know many clinicians loathe to hear patients attempt to self-diagnose…but we’ll put those matters aside for today and do a brief rundown of the tools of this type.
MEDgle starts the user out by entering any number of symptoms and the symptoms’ duration as well as the user’s sex, age range, and whether the user is a smoker of overweight, then having the user narrow the search by selecting body parts or symptoms. The search field auto-completes your search term. When the diagnosis has been determined, search results are shown from outside of MEDgle. Of course, there’s a disclaimer: “Medgle is…is not a diagnostic or decision making tool.”
Of course, this isn’t a new idea to anyone with access to McGraw-Hill’s Access Medicine. Access Medicine, after all, includes the Diagnosaurus.
Diagnosaurus provides differential diagnoses (DDx) of symptoms, signs, and diseases. By using the pulldown menu, you can choose to view entries by organ system, or select to view the list of symptoms only, the list of diseases only, or all of the entries. For example, if you wish to review the causes of a patient’s chief complaint, simply select the symptom or sign from the alphabetical listing. If you have made a diagnosis and wonder what other disorders to consider, select your diagnosis from the list to see its DDx.
Diagnosaurus is also available as a download for your PDA.
Healthline Symptom Search has a really good how it works page. Like MEDgle, it’ll auto-complete your entered symptom, or you can choose from a drop-down list of 50 common symptoms. Also like MEDgle, you can search by multiple symptoms in a smooth, AJAX-y interface.
MedicineNet.com’s Symptoms and Signs doesn’t have the cool auto-completing interface and you can only search by one symptom at a time.
FamilyDoctor.org’s Search by Symptom isn’t really a search by symptom service….really more of a “browse by a very short list of symptoms” service.
The Mayo Clinic Symptom Checker (also licensed to Revolution Health) lets the user start with a single symptom, then narrow down on potential diagnosis by checking boxes to indicate additional information about your symptoms.
WebMD’s symptomchecker lets the user select a part of the body by clicking on a picture to zoom in, then select a more specific part before being offered a list of symptoms one can add to one’s list.
From here, it looks like Mayo, MEDgle, Healthline and WebMD are all hard at work making “Self-Diagnosis 2.0” where Diagnosaurus, MedicineNet.com and Family Doctor are way, way behind.
Questions for readers:
I often stumble across good and useful things by accident.
Case in point: While using Google to look for a document I had misplaced, a typo caused me to stumble across an article from the March 2007 issue of the CILIP Health Libraries Group Newsletter titled “Internet Sites of Interest,” featuring short descriptions of a number if third-party PubMed tools. I recognized the name of the author, Keith Nockels, because I have subscribed to his blog’s feed since I first discovered it through the Masterlist of MedLib Blogs.
I recently wrote a similar item for publication, but selected a completely different set of tools to focus on- so it was loads of fun to see which ones Keith decided to feature. (Mark Rabnett recently wrote a similar piece. Again, there is very little overlap between his selections and mine.)
Snag Keith’s article here: PDF
Now that I know this newsletter exists, I’ll be keeping an eye out for future issues. Thanks, Keith!
Quick question I’m hoping a U.K. Health Librarian will answer: I understand that CILIP is to the U.K. what the ALA is the U.S.. Is the HLG the closest U.K. analogue to the U.S.’s MLA? If you’re not sick to death of acronyms and initialisms yet, please leave me a comment and let me know? Many thanks!
Ali Baba is pretty neat.
Ali Baba parses PubMed abstracts for biological objects and their relations as discussed in the texts. Ali Baba visualizes the resulting network in graphical form, thus presenting a quick overview over all information contained in the abstracts.
Perhaps the best way to explain what it does is with an example:
A patient with cough is treated with codeine. He becomes unresponsive after a while — what is going on?
The query entered in Ali Baba was “codeine intoxication”.
Ali Baba shows the relationship between codeine (marked in the graph with blue frame), cough, morphine, and poisioning. Poisioning is also connected to morphine and CYP2D6. The solution thus is that codeine is bioactivated by CYP2D6 into morphine, certain patients show an ultrarapid form of this metabolism, which leads to a life-threatening intoxication (see Gasche et al. (2004)). The connection codeine->CYP2D6->morphine is directly visible in Ali Baba.
To make this example a bit more concise and focused on the central problem, we used the minimum degree filter (in the menu, see Preferences|Filter preferences). This allows to remove all nodes without any neighbors (unconnected nodes) using the ‘Degree’ slider on the bottom panel.
I’m not sure Ali Baba will be of any use to me, but it really is neat. Please note: Ali Baba requires Java 1.5 or higher.
MeshPubMed is a (new?) third-party search tool for PubMed.
- retrieves PubMed abstracts for your keywords,
- detects Medical Subject Headings (MeSH) in the abstracts,
- displays a subset of MeSH relevant to your search, and
- allows you to browse the ontology and display only papers containing specific MeSH terms.
After performing a search, the resulting abstracts are annotated with your query keywords and MeSH terms. The abstracts are grouped using the MeSH terms, which appear in the text. You can use the MeSH hierarchy to systematically explore your search results.
Note that only a subset of all terms may be relevant to your query. This subset – the hierarchy of relevant terms – is presented on the left hand side. Sorting documents to a highly organised network facilitates the finding of relevant documents significantly.
I’m not the first to blog about these and I certainly won’t be the last, but I wanted to say a few brief “me too’s”:
I’m going to order Social Software in Libraries…
…and not just because Meredith mentions LibWorm in Chapter Three, either! I’m going to order it because Meredith’s writings on technology (at both her own blog and at TechEssence) are smart, clear and practical- and they don’t leave out the human element. I expect her book will have similar qualities.
I won’t go so far as to recommend that others purchase a book that I haven’t myself yet read, but I will say that I am definitely ordering my copy the instant I can.. [Other biblioblog chatter about this book]
I will also need to buy a copy of Phil Bradley’s new book, How to Use Web 2.0 in Your Library:
Like Meredith’s book, Phil’s has a companion Web site, and also mentions LibWorm (curiously, also in Chapter Three). I subscribe to Phil’s blog and routinely learn new things from him, so I can’t be without this book. I just hope it gets published in the States, too- the exchange rates from Pound to Dollar and shipping from the U.K. are probably going to be painful.
Lastly, I’m going to order a copy of this book :
While I don’t yet have any indication that it mentions LibWorm ( 😉 ) and I’m still not yet wholly comfortable with the term “Library 2.0”, everything I’ve read that Casey and/or Savastinuk have written on the topic has been thought-provoking, required reading. I wouldn’t miss getting my own copy for any reason. [Other biblioblog chatter about this book]
 – It goes without saying that if Meredith wants to send me a copy, I will of course devour it and write a detailed review.
 – Naturally, the same offer is extended to Phil.
 – Ditto for Michael and Laura.
I’d also be willing to write a review for a publication if it means I get to keep a copy of any of these.
(I’m subtle, huh? My subtlety is inversely proportionate to my budget for discretionary spending.)
I’ve been looking at BioWizard more. I still think it is a great idea executed well, but I’m seeing a couple of problems with its “tags”.
They’re not really tags
The first problem is that the word “tags” implies that the terms assigned to each article are a part of a user-created folksonomy, but this isn’t actually the case. If you look at the citation for PubMed ID 17146093, you’ll see it was indexed with these MeSH terms:
So, calling these “tags” is a disservice both to people who know what MeSH terms are, and to users accustomed to participating in the creation of folksonomies with user-generated tags.
Missing MeSH terms
Rachel Walden noticed instances where articles that have been indexed in PubMed with MeSH terms, but those terms do not appear in BioWizard as tags. The best guess we came up with was that these articles were submitted to BioWizard by users when their citations were in-process.
Suggestions for the good folks at BioWizard
Previous related posts:
There’s lots of interesting content in this latest issue of the Journal of the European Association for Health Information and Libraries, but I’m especially intrigued by Guus van den Brekel’s article on The Changing of the User Environment (tenth PDF page, numbered page eight).
I only gave it the one quick read, but that was enough to make certain I’d read it again more slowly later. Since I couldn’t fly to Norway to see Guus present the paper, I’m glad he has shared it in print.
Thanks for the heads-up, Benoit!
Created by Michael Wesch, Professor of Cultural Anthropology at Kansas State University.