جستجوی مقالات مرتبط با کلیدواژه « medical information storage » در نشریات گروه « پزشکی »

One of the ways to retrieve the expert information from Internet, is using search tools. The objective of is this research is to measure the relevance of documents retrieved from search engines and meta search engines in the field of Dentistry and assesse the accuracy of given data.
Material & This research was done in descriptive survey method. 5 major search engines and 5 Meta search engines that are introduced by the website of www.searchenginewatch.com as well-used search tools of Internet were chosen. Dentistry keywords were chosen from medical subject Headings (Mesh) 2010 version and then selected terms of Dentistry were searched in each search engines. The first 10 results of search engines were selected for evaluation of recall and precision. Data collection was prepared through direct observation. Searching was conducted using selected keywords of dentistry field in each search engine. First 10 results were selected to evaluate the comprehensiveness and blocking. Data were analyzed using Excell & R version 3.3.1 and SPSS version 22.
Yahoo retrieved the most Dentistry documents and scored the highest rank (66%). Ask had (70%) precision and (30%) recall and retrieved the most relevant Dentistry documents. Clusty retrieved the most Dentistry documents and scored the highest rank (47%). Clusty with (66%) precision and (33%) recall retrieved the most relevant Dentistry documents. For retrieval of Dentistry information, there were significant difference for comprehensiveness between search engines and meta search engines at significance level of 0.05 and level of R software was more than critical point. So, equality of ratio hypothesis was not accept.
Regarding given results, Meta search engines are suitable tools for amateur or professional users and they have suitable search capabilities and facilities might be used to access the relevant documents in the field of Dentistry.

This research aimed at determining and comparing the precision and recall of general search engines to retrieve images of important diseases in the field of endocrinology.

An analaytical survey was conducted in this applied research, for which 50 keywords in the field of 5 endocrine diseases were selected, and the 30 top images retrieved by each search engine were stored and analyzed, using precision and recall measurement formulas and excel software.

This research show that Google search engine has the most percision (35%) followed by the Bing and Yahoo search engines. Images retrieved for adrenal diseases had the most percision (42%) in google while it was (16%) in yahoo. The Bing search engine had the most recall (77%), followed by the google and yahoo search engines. Diabetes mellitus had the most recall (97%) in the google and bing search engines. Adrenal diseases had the least recall (30%) using yahoo search engine.

Results show that Google and bing search engines were in competition with each other and professionals of endocrinology and other researchers can use these search engines, Google and bing in particular, to retrieve the best medical images. Librarians also can use and recommend these two search engines to related professionals for retrieving medical images of adrenal, pituitary, thyroid, diabetes and para-thyroid diseases.

The huge volume of information and images on the Internet and its increasing growth has made the optimized search performance difficult for users. Among search tools, search engines are mostly used by users. This research was aimed to determine and compare the precision of general and specialized search engines in medical images retrieval.

This applied, comparative approach survey was conducted in 2011. The research sample included 2 general search engines, i.e. Yahoo and Google, and 2 specialized medical search engines, i.e. OmniMedicalSearch and Trip Database. In order to determine and compare the precision of image retrieval in the four search engines, 10 medical keywords were chosen after consulting medical specialists and were searched in the mentioned search engines. Then the first 10 results retrieved by each search engine were extracted and the opinions of medical specialists about relevance of results were received. Descriptive statistics, Independent t-test were used to analyze the data with SPSS.

It was found that Google search engine has the most precision (90) in retrieving of relevant medical images and then OmniMedicalSearch search engine has precision to be equal 86/8. Among general search engines and specialized medical search engines there aren’t meaningful differences in retrieval of medical images.

Despite of some overlap between search engines results, each search engine also was retrieved unique results. This matter indicate that the indexing algorithm of resources on the web different in the various search engines; and it is suggested to use several general and specialized search engines simultaneously to search medical images.

The aim of each information retrieval is to present relevant information to the right user at the right time. Images as a kind of information can convey a large volume of information. In medicine، the most common use of images is in education، research and medical diagnosis. This wide variety of usage refers to the uprising importance of imaging through various fields of medicine. Therefore، current advances in medical imaging techniques and frequent use for example، in decision making systems and evidence-based medicine depicts the high necessity of medical images retrieval. This paper introduced text-based and content-based image retrieval systems، the application of the image systems especially in medicine. Some existing systems are described. Finally it was suggested although images have some features different from texts but some techniques in text retrieval such as artificial intelligence and relevance feedback can be used to improve the image retrieval systems.