Babelmesh is a multi-language tool for searching NLM's MEDLINE/PubMed. It has the following features:
- It is intended for users whose native languages is not English.
- Queries can be submitted as single terms or complex phrases in one of the languages listed below.
- The search interface changes to allow search terms to be entered in the chosen language.
- Typing accents or other diacritical marks is optional.
- Queries are transformed into English. Results are MEDLINE/PubMed citations published in any one or more of the listed languages, as specified by the user.
- Links to full-text articles, if available for free, are included in the search results.
Babelmesh is available at (http://pubmedhh.nlm.nih.gov/babelmesh/index.php ).
Consensus Abstracts is a Web interface formatted for wireless mobile devices (for example, cell phones, smartphones, and tablet computers) for searching MEDLINE/PubMed.
It is available through PubMed for Handhelds ( https://pubmedhh.nlm.nih.gov/pico/consensus.php ), from which either askMEDLINE or PICO can be used to initiate a Consensus Abstracts search:
- With askMEDLINE, a user enters free-text, natural language terms. An example is “For a child with acute abdominal pain, will analgesics mask the diagnosis of acute appendicitis?”
- From PICO (Patient, Intervention, Comparison, and Outcome), a user fills in one or more of a Medical condition, an Intervention (therapy, diagnostic text, etc.), an optional Compare to, and an optional Outcome. The user can also select a publication type from among Clinical Trial, Meta-Analysis, Randomized Controled Trial, Systematic Reviews, and Review, and Practice Guideline.
Consensus Abstracts displays retrieved MEDLINE/PubMed articles as a list of journal citations (author, title, publication date, PubMed ID). A checkbox next to each item allows the user to choose citations of interest or, if the first series of articles are acceptable, those articles can be selected for display through a "Submit" button, or the exact number of articles can be entered.
Consensus Abstracts then presents, on a results Web page, the summaries of each abstract found by The Bottom Line (TBL) (also available through PubMed for Handhelds); the search terms and publication types are also displayed. TBL results and full abstracts can also be displayed on the results page by clicking on links, so a user doesn't have to leave that page. Full-text articles, if available, and lists of related articles can be retrieved through links from citations.
The I-MAGIC (Interactive Map-Assisted Generation of ICD Codes) Algorithm utilizes the SNOMED CT to ICD-10-CM Map in a real-time, interactive manner to generate ICD-10-CM codes. This demo simulates a problem list interface in which the user enters problems with SNOMED CT terms, which are then used to derive ICD-10-CM codes using the Map.
The Map can be used in the following scenarios:
- Real-time use by the healthcare provider – In this scenario, the Map is embedded in the problem list application of the EHR used by the physician or other healthcare provider. At the end of a clinic encounter, the clinician updates the problem list, which is encoded in SNOMED CT. The Map-enabled problem list application outputs a list of ICD-10-CM codes based on algorithmic evaluation of map rules, which makes use of patient context (e.g. age, gender) and co-morbidities (other problems on the problem list) to identify the most appropriate candidate ICD-10-CM codes, in accordance with ICD-10-CM coding guidelines and conventions. If necessary, the clinician is prompted for additional information to decide between alternative codes, or to refine the output codes. The clinician confirms the suggested ICD-10-CM codes. (See the I-MAGIC algorithm and demo page)
- Retrospective coding by coding professionals – In this scenario, the Map is used within an application to suggest candidate ICD-10-CM codes to coding professionals based on a stored SNOMED CT encoded problem list. The degree of automation can vary. Textual advice can be displayed in cases where automated rule processing is not available.
- Web Interface: http://imagic.nlm.nih.gov/imagic/code/map
- I-MAGIC Implementation Guide: http://www.nlm.nih.gov/research/umls/mapping_projects/IMAGICImplementationGuide_20120614.pdf
- About the SNOMED CT to ICD-10-CM map: http://www.nlm.nih.gov/research/umls/mapping_projects/snomedct_to_icd10cm.html
The SPECIALIST lexical tools are a set of JAVA programs designed to help users manage lexical variation in biomedical text. The tools use information from the SPECIALIST lexicon and other data to generate lexical variants of words or terms appropriate for use in indexing and other NLP applications.
Try Lexical Web Tools online.
Consult the MetaMap page to learn about the myriad ways to use this tool.
The Open-i project aims to provide next generation information retrieval services for biomedical articles from the full text collections such as PubMed Central. It is unique in its ability to index both the text and images in the articles. The article retrieval is powered by Essie (the search engine that supports ClinicalTrials.gov).
Open-i lets users retrieve not only the MEDLINE citation information, but also the outcome statements in the article and the most relevant figure from it. Further, it is possible to use the figure as a query component to find other relevant images or other visually similar images. Future stages aim to provide image region-of-interest (ROI) based querying. The initial number of images is projected to be around 600,000 and will scale to millions. The extensive image analysis and indexing and deep text analysis and indexing require distributed computing. At the request of the Board of Scientific Counselors, we intend to make the image computation services available as a NLM service.
Vist our Frequently Asked Questions page for more information and help.
Web Interface: https://openi.nlm.nih.gov/
RxMix has been updated! RxMix is a web application that allows users to combine functions from the RxNorm, NDF-RT and RxTerms APIs to create custom applications that can be run interactively or in a batch mode.
- Function composition. The RxMix interface allows the user to build a workflow of API functions to execute. This saves the user from having to write complex programs to handle multiple function calls. Examples of function composition are contained in the examples below.
- Batch processing. Through the user interface, RxMix allows the user to process large amounts of data through the user defined workflow. The user can provide a file containing a list of inputs, such as drug names or drug identifiers, for input to the workflow. RxMix will execute the workflow and inform the user via email when the job has completed, providing information on how to retrieve the results.
- Output in XML, JSON or Text. RxMix offers the user the choice of formatting the output in XML, JSON, or text.
- Interactive mode. RxMix allows users to interactively test and display the results of the workflow on a single input value.
**Note: RxMix will not work properly with Internet Explorer. Please use FireFox, Chrome or Safari to run RxMix.
- Web interface: http://mor.nlm.nih.gov/RxMix/
- Learn More: http://rxnav.nlm.nih.gov/RxMixTutorial.html
- RxMix Tutorial Batch Example: http://rxnav.nlm.nih.gov/RxMixTutorial2.html
RxNav is a browser for several drug information sources, including RxNorm, RxTerms and NDF-RT. RxNav finds drugs in RxNorm from the names and codes in its constituent vocabularies. RxNav displays links from clinical drugs, both branded and generic, to their active ingredients, drug components and related brand names. RxNav also provides lists of NDC codes and links to package inserts in DailyMed. The RxTerms record for a given drug can be accessed through RxNav, as well as clinical information from NDF-RT, including pharmacologic classes, mechanisms of action, and physiologic effects.
- Web Interface: https://mor.nlm.nih.gov/RxNav/
The SKR project maintains a database of 96.3 million SemRep predications extracted from all MEDLINE citations. This database supports the Semantic MEDLINE web application, which integrates PubMed searching, SemRep predications, automatic summarization, and data visualization. The application is intended to help users manage the results of PubMed searches. Output is visualized as an informative graph with links to the original MEDLINE citations.>/p>
To access any of the SemRep/SemMedDB/SKR Data Sets or the SemMedDB Database, users must have accepted the terms of the UMLS Metathesaurus License Agreement, which requires users to respect the copyrights of the constituent vocabularies and to file a brief annual report on their use of the UMLS. Users must also have activated a UMLS Terminology Services (UTS) account. For information on how to use UTS authentication, please click here.
To download the SemMedDB Database click here.
To run the Semantic MEDLINE web application click here.