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Patent Searching in Scopus

Similar to Web of Science, Scopus is a multidisciplinary database that covers journal articles, conference proceedings, and books and allows citation analysis. A lesser known feature in Scopus is patent searching. There are about 23 million patent records in Scopus, derived from five patent offices, including the US Patent & Trademark Office, the European Patent Office, the Japan Patent Office, the World Intellectual Property Organization and the UK Intellectual Property Office*.

For patent searching, conduct your search as you normally would either using the default Document Search or using other options such as Author Search and Affiliation Search. On the results page, you will see the number (7,655 in the example showed in the screenshot) of Documents Results listed on the upper left side of the screen. To the right of this number, there is a link that says “View 358 patent results”. This link will take you to a separate page with patents listed. Note that the patent link will only appear if there are patent results that matched your search terms.

Patent searching in Scopus screenshot

To know more about patents and how to find them, visit the Patent guide created at the Lichtenberger Engineering Library. You can also take a patent class at Hardin Library; for more information, visit the Hardin Open Workshops website at http://www.lib.uiowa.edu/hardin/workshop/.

*Source: Elsevier. Scopus Facts & Figure Factsheet. http://www.elsevier.com/__data/assets/pdf_file/0007/148714/3859-Scopus-Facts-and-Figures-LO.pdf  Accessed April 28, 2015.

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CINAHL, DynaMed and Other EBSCO Databases Available Off-Campus

EBSCO databases including CINAHL and DynaMed should now be working from off-campus.

If you have questions or comments, please don’t hesitate to contact us.

 

 

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Embase: Tips For Navigating A Powerful & Tricky Resource

By Eric Rumsey
Embase, which we described in an earlier article, is a powerful biomedical database which is comparable to PubMed. Unfortunately, the interface for Embase is rather difficult to navigate, especially for new users. We have created two resources for beginning users:

A 2-page handout: Basic Searching in EMBASE

A slide set that shows the first steps in doing a successful search in Embase: Embase: Use Quick Search To Do Mapping!

A slide set that shows the steps to do a simple search on heart attack and aspirin: Embase Searching- A Basic Tutorial

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New Resource: Cochrane Clinical Answers

The library now has a subscription to Cochrane Clinical Answers (CCAs). CCAs are derived from Cochrane systematic reviews and provide clinicians with short answers to clinical questions at the point of care.The website allows browsing by disease categories and keyword searching. Each CCA contains a clinical question, a short answer, and links to relevant Cochrane systematic reviews. See the screenshot below for an example.  Note that CCAs are still in development, and there is not a CCA for every Cochrane systematic review.

Similar resources to be used by clinician at the point of care include DynaMed and UpToDate, both of which can be found at the Health Sciences Resources A-Z page.

Questions? Comments? Email us at lib-hardin@uiowa.edu or call (319) 335-9151.

CCA screenshot

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Searching Nutrition In PubMed & Embase: The Winner Is…

By Eric Rumsey and Janna Lawrence

As we’ve discussed, the big problem in searching for food-diet-nutrition subjects in PubMed is that the subjects are not together in a convenient bundle, as most subject groupings are in PubMed. To get a list of articles that includes food, diet and nutrition, it’s necessary to search each of these areas separately and then bundle them together into one search set.

When we first wrote about the difficulty of searching food-diet-nutrition in PubMed in 2013, we stated clearly that much of problem is caused by the fragmentation of the the relevant MeSH terms. So, jump forward a year. About two months ago, our library got institutional access to Embase.com, sometimes called the “European MEDLINE.” Embase includes all of the articles in MEDLINE, as well as many other articles, and uses its own subject heading system. Because we’ve long been aware that food-diet-nutrition subjects are generally given more attention in Europe than in the US, we thought that the subject might get better treatment in Embase than it does in PubMed. We weren’t disappointed…

A Nutrition explosion that includes Food and Diet

Embase uses explosions to bundle related subjects together, much like PubMed, and, as we were hoping, it does indeed bring food, diet and nutrition subjects together in a convenient bundle – Nutrition. So in the search box, just type in Nutrition/exp to get the nutrition explosion, that will retrieve everything on food and diet as well as nutrition. This is a great advance over PubMed. It becomes easy to combine a subject of interest with food-diet-nutrition, in one simple step. For example, using Embase.com format:

‘Heart disease’/exp AND Nutrition/exp
Neoplasm/exp AND Nutrition/exp
‘Mental function’/exp AND Nutrition/exp

To do equivalent searches in PubMed, it’s necessary to do a hedge/filter search, such we have developed, or to search food-diet-nutrition terms separately and combine these with the subject of interest.

Better treatment of “Food” in Embase

Certainly having the inclusive food-diet-nutrition explosion is the biggest advantage in Embase. But there are other problems in PubMed, especially in the way the Food explosion is treated. In both Embase and PubMed, Food is the largest food-diet-nutrition explosion. There are several difficulties with this explosion in PubMed. An overall complication is that Food and Beverages have a confusing relationship. They are together in one explosion Food and beverages, which is made up of two separate explosions, one for each of the terms. If the user knows enough to search Food and beverages, he/she will get both terms. But if the user searches “Food,” the search will not include beverages. In Embase, beverage is an explosion that’s included in the food explosion, so searching “food” will retrieve articles on beverages.

Several other problems with the Food explosion in PubMed are caused by a lack of detail, in comparison with Embase. Some examples:

  • In PubMed, Fruit is not an explosion, although there are individual fruits included in the Plants explosion, usually under their Latin plant name. In Embase, the fruit explosion has 43 terms under it, 6 of which are themselves explosions.
  • In PubMed, Spices is an explosion with one term under it – Black Pepper. In Embase, the spice explosion has 31 terms listed under it, 4 of which are themselves explosions.
  • In PubMed, specific kinds of red meat, e.g. beef and pork, do not have their own MeSH terms; instead, they’re indexed under the general term Meat. In Embase, the meat explosion contains a red meat explosion, which has 7 terms, including beef and pork.

Related to the lack of detail in the Food explosion in PubMed is that many foods, especially plant-based foods, are not retrieved in a search for “food” because they don’t have specific terms in the Food explosion. We have written some “case studies” of this on chocolate, cranberries, and olive oil, all of which are in the Food explosion in Embase, but not in PubMed. We have also written an article on red meat being difficult to search in PubMed because there is no MeSH term for it; as mentioned above, Embase does have a term for it.

Looking at articles in Embase and PubMed that mention specific foods in the article abstract, it’s almost always the case that Embase’s detailed indexing will include descriptor terms for the specific foods, and PubMed usually will not. Comparison of article indexing is easy to do because Embase provides a “Source” filter, that makes it possible to limit to articles that are included in both Embase and PubMed. Each of the articles retrieved using this filter has a direct link to the citation in PubMed.

PubMed Advantages

The biggest advantage of PubMed, of course, is that it’s free to world. Embase, on the other hand, is an Elsevier product and is only available at institutions that have a subscription.

Another PubMed advantage is its simple Google-like interface, which is certainly more comfortable to most people. Embase uses an older style of interface that may appeal to librarians more than to most users. For anyone with a serious interest in food-diet-nutrition, though, we would say it’s definitely worth learning.

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New Resource: Board Vitals

Board Vitals Logo

Board Vitals is an exam preparation database. At this time, Hardin Library has subscribed to question banks for: Dermatology, Emergency Medicine, Neurology Shelf Exam, OB-GYN Shelf Exam, Otolaryngology, Pathology, Psychiatry, Psychiatry Vignettes, Child and Adolescent Psychiatry, and Radiology.

According to Board Vitals: “we provide up-to-date explanations from the literature with our answers and give you detailed feedback and assessment of your progress broken down by subject areas. With each question you can see how you compare to your peers, and gauge the difficulty of the question by what percentage of your peers answered it correctly or chose the same option you did.”

To use Board Vitals, you will need to:

  1. Access Board Vitals via the health science resources page: http://www.lib.uiowa.edu/hardin/eresources/
  2. Click the link that says “If Signing Up for the First Time, Click Here.”
  3. Fill out the form and you are ready to go.

You will have the option to select an area and then build a custom exam. The number of questions available is listed, and you can choose between a review or a timed exam. The reviewed exam provides explanations whether you answer the question or not. It will also show you how many exam takers correctly answered the question.

You can choose to answer between 1-50 questions, and, once you’ve used the resource, you’ll notice that you can choose to answer new questions, all questions, or incorrect questions.

Board Vitals is only one of the resources that Hardin Library provides for exam preparation. To find out about other resources, check out our Board Review Materials LibGuide http://guides.lib.uiowa.edu/boardreview

As always, please feel free to contact us http://www.lib.uiowa.edu/hardin/contact if you have any questions, comments, or concerns.

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New AccessMedicine App

AccessMedicine Screenshot

AccessMedicine is a collection of clinical tools and electronic textbooks. The app is powered by Unbound Medicine and provides access to a small portion of AccessMedicine.

The included resources are:

Quick Medical Dx and RX – Contains evidence-based outlines of conditions and disorders most often encountered in medical practice.

Fitzpatrick’s Color Atlas of Clinical Dermatology – This landmark digital reference facilitates visual diagnosis by providing color images of skin lesions, plus a summary outline of skin disorders and diseases.

Diagnosaurus – A differential diagnosis tool with more than 1,000 diagnoses. Browse by symptom, disease, or organ system.

Pocket Guide to Diagnostic Tests – This handy guide is a quick reference to the selection and interpretation of commonly used diagnostic tests include laboratory procedures in the clinical setting.

This app is available for Android and iOS (iPhone, iPad, iPod Touch) devices. In order to download and continue to access to the app, you must have an active AccessMedicine account and sign in every 90 days through Hardin Library.

 1.       Go to AccessMedicine via Hardin Library http://purl.lib.uiowa.edu/accessmed

2.       Create an account by clicking on the box at the top right of the screen that says “Univ of Iowa Hardin Library.”

3.       Select “Login or Create a Free Personal Account.”

4.       Once you have your username and login, download the app from Google Play or the iTunes App store.

5.       Login with your AccessMedicine Account.

As always, if you have questions, comments, or concerns, please do not hesitate to contact us.

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Plant-Based Foods – An Inclusive PubMed Search

By Eric Rumsey and Janna Lawrence

In our earlier article on searching for plant-based foods (PBF) in PubMed, we suggested that a quick way to search the subject is to combine MeSH plant-related explosions AND our Food-Diet-Nutrition (FDN) hedge. This works quite well, especially for citations after 2002. In that year the Plants explosion was greatly expanded by the addition of several hundred new MeSH plant names. Before that, articles on specific plants were indexed inconsistently. Sometimes they were put under the plant family name, in which case they were included in the Plants explosion, and in other cases they were indexed under other terms like Vegetables, Fruit, or Plants, Edible, that are not in the Plants explosion.

In order to do the most inclusive search for plant-based foods, including citations before 2002, we have created two hedges, to be used for all the years in PubMed. These hedges include other MeSH terms and text-words, to supplement the plant-related MeSH term search strategy that works well after 2002. We have done fairly thorough testing of the two hedges, and we recommend the first hedge for most searches. It uses MeSH terms, and it emphasizes precision, which means that it gets somewhat fewer citations, but the citations are more likely to be on target. For both of the hedges, we’ve combined them in an OR search with the “Plants AND FDN” hedge search mentioned above.

Here’s the first hedge – Recommended for most searches – Emphasizes Precision:

((Plants [mesh] OR Plant Preparations [mesh]) AND (food OR foods OR beverages OR diet OR dietary OR vitamin OR vitamins OR nutrition OR nutritional OR nutrition disorders OR food industry OR nutritional physiological phenomena OR dietary fats OR dietary proteins OR feeding behavior)) OR (Vegetables [mesh] OR Fruit [mesh] OR Cereals [mesh] OR Plants, Edible [mesh] OR Soybeans [mesh] OR Dietary Fiber [mesh] OR Flour [mesh] OR Bread [mesh] OR Diet, Vegetarian [mesh] OR Nuts [mesh] OR Condiments [mesh] OR Vegetable Proteins [mesh] OR Tea [mesh] OR Coffee [mesh] OR Wine [mesh])

[9.5.14. Hedge revised - Number of citations: 294,149]

To use this search, click this link. You can also copy the text above and paste it into the PubMed search box. If you have a personal “My NCBI” account in PubMed, the hedge search can be saved for later use, or it can be made into a search filter. For information on setting up and using saved searches, see here; for more information on filters, see here. Commentary on terms in this hedge (If the “Year introduced” is not given, the term has been in MeSH since its launch in 1966):

  • Vegetables [mesh] Citations: 84411 An explosion that includes about 25 specific vegetables, including Onions, Soybeans, Daucus carota, and Solanum tuberosum. This is a relatively small proportion of all vegetables, which are indexed with their species or family name, in the Plants explosion.
  • Fruit [mesh] Citations: 57179 Notably, this is NOT an explosion. All particular fruit types are indexed with their species or family name, in the Plants explosion.
  • Cereals [mesh] Citations: 73516 An explosion that includes 8 cereals, including Avena sativa, Triticum and Zea mays. This is an important group, since it includes the world’s staple foods–wheat, rice, and corn.
  • Plants, Edible [mesh] Citations: 38945 An explosion that includes several terms elsewhere in this hedge that get more citations when they’re searched separately. The term Plants, Edible by itself gets 5402 citations.
  • Soybeans [mesh] Year introduced: 1986 Citations: 19284 An explosion that includes Soy Foods, Soy Milk, and Soybean Proteins.
  • Dietary Fiber [mesh] Year introduced: 1982(1977) Citations: 13468
  • Flour [mesh] Citations: 3570
  • Bread [mesh] Citations: 3115
  • Diet, Vegetarian [mesh] Year introduced: 2003(1963) Citations: 2537
  • Nuts [mesh] Citations: 2074
  • Condiments [mesh] Citations: 1945 An explosion that includes Spices.
  • Vegetable Proteins [mesh] Year introduced: 1975 Citations: 1515
  • Tea [mesh] Citations: 6904
  • Coffee [mesh] Citations: 4751
  • Wine [mesh] Citations: 7256

Here’s the second hedge - Emphasizes Recall:

((Plants [mesh] OR Plant Preparations [mesh]) AND (food OR foods OR beverages OR diet OR dietary OR vitamin OR vitamins OR nutrition OR nutritional OR nutrition disorders OR food industry OR nutritional physiological phenomena OR dietary fats OR dietary proteins OR feeding behavior)) OR (vegetable OR vegetables OR fruit OR fruits OR cereal OR cereals OR spices OR condiments OR flour OR nut OR nuts OR vegetarian OR soy OR soybean OR soybeans OR bread OR Tea OR Coffee OR Wine)

[9.5.14. Hedge revised - Number of citations: 380,361]

To use this search, click this link, or see instructions above with first hedge. Most of the words used in this hedge are text-word versions of the MeSH terms used in the first hedge. Since this emphasizes “recall” instead of “precision,” it gets more citations than the first hedge. But the citations are less likely to be relevant. We looked closely at citations using the two hedges, and it was easy to see the lesser relevancy of the citations in the second hedge. Most of these, of course, are retrieved because they mention words that are in the abstract (e.g. fruit, vegetables) but which are not assigned as MeSH terms.

A word about searching for older citations

When we first realized that most of the plant name MeSH terms were only introduced in 2002, it seemed like a serious problem. However, as we’ve looked back retrospectively, we’ve come to see that there really wasn’t much research attention given to the subject in the earlier days of MEDLINE, especially before about 1990.

We’ve done detailed work to study this, but in this article we’ll just give a couple of anecdotal examples of what we’ve found. We looked at the number of citations that contain the word “fruit” since 1968, and found that this stayed flat, at about 400 mentions per year, until about 1990. It’s grown fast since then, and in 2013, the word is in about 8000 citations. In another example, we found that there are 70 articles in all of PubMed that have “sweet potato” in the title, and are on human subjects. All but three of these are after 1992; zero citations from 1980-1992 contain the words in the title. So, if it seems like the hedges in this article aren’t finding many citations before 1990, it’s probably because there just aren’t many to be found.

Things improve in the 1990s. It appears, from our retrospective examination of citations on FDN, that as the volume of research on the subject increased, NLM gradually improved the quality of MeSH indexing to accommodate it. The coverage of more prominent plant families improved, and the application of existing FDN MeSH terms became more consistent. So in the 1990s, even before the mass introduction of new MeSH plant terms in 2002, FDN indexing and retrieval was improving.

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PubMed Food Problem: Red Meat

By Eric Rumsey and Janna Lawrence

As we’ve discussed before, searching for “red meat” in PubMed is difficult because the subject is poorly covered in the MeSH vocabulary. Not only is there not a term for “red meat,” but there are also no MeSH terms for specific kinds of red meat (beef, pork, etc.). There is only the one all-inclusive MeSH term Meat, which includes all kinds of meat, as well as fish and poultry. So this is a rare case in PubMed in which MeSH is essentially useless. The only way to do a thorough search is to use text words that include the phrase “red meat” or that contain specific types of red meat – e.g. “red meat” OR beef OR pork… [etc]

The problem of searching for red meat has returned to our attention recently for two reasons. One is that the subject continues to be in the news. Last winter when we wrote, it was getting attention because red-meat nutrient carnitine was reported to be linked to heart disease. And recently red meat has been back in the news because it’s been reported that tick bites can trigger an allergy to red meats.

The other reason we’ve been thinking about red meat is that, coincidentally, our library has recently gotten a subscription to Embase, which a European-based medical literature database that’s the main alternative to PubMed/MEDLINE. Of course, the first thing we did with new access was to compare the indexing, and especially the explosions, in Embase to PubMed for Food-Diet-Nutrition subjects. We have found several cases in which Embase is better. One case in which it’s clearly better is red meat.

Here’s the explosion in Embase:

Red Meat
… Beef
… Lamb Meat
… Mutton
… Pork
… Rabbit Meat
… Veal
… Venison

This can’t be used directly in PubMed, of course, but at least it gives an idea of specific meats to search in PubMed as text words.

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MeSH on Demand Tool Launched

The National Library of Medicine (NLM) recently launched a new tool called MeSH on Demand. Now, you can find MeSH terms from text you input! MeSH on Demand is available online in the MeSH Browser.

First, input up to 10,000 characters of text into MeSH on Demand, your text will be processed using the NLM Medical Text Indexer (MTI) program.

mesh on demand example

Then, MeSH on Demand will identify MeSH Headings, Publication Types, and Supplementary Concepts from your text.  Qualifiers (subheadings) are not identified.

mesh on demand results

Disclaimer:
MeSH terms are machine-generated without human review.  Results will be different from human-generated indexing.

Comments:
The  NLM welcomes questions and comments about MeSH on Demand.  Fill out a contact form:  http://apps2.nlm.nih.gov/mainweb/siebel/nlm/index.cfm/