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MedNar

MedNar

MEDIE MEDIE is an intelligent search engine to retrieve biomedical correlations from MEDLINE, based on indexing by Natural Language Processing and Text Mining techniques. You can find abstracts/sentences in MEDLINE by specifying semantics of correlations; for example, "What activates p53" and "What causes colon cancer". Semantic search is to use a semantic query for finding biomedical correlations. Input a subject, a verb, and an object of a concept (or either of them) into a form. Results of the query will be shown in a second. Examples: "What does p53 activate?" A GCL query is directly passed to a GCL server. The customization of the number of results is available as in Semantic Search. A list of GCL operators: Go to top This system is provided by the Tsujii Laboratory "AS IS" without warranty of any kind. This system is built on the Medline database leased from the National Library of Medicine [NLM]. NLM represents that its data were formulated with a reasonable standard of care.

Medicine | Ebooks 2012 German | ISBN: 3709104661 | 2013 | 550 pages | PDF | 11 MB Das Buch liefert eine ubersichtliche und pragnante Darstellung der diagnostischen und therapeutischen Rehabilitationskonzepte fur zahlreiche Krankheitsbilder. Fur die 3. Download [Fast Download] Kompendium Physikalische Medizin und Rehabilitation: Diagnostische und therapeutische Konzepte, Auflage: 3 2012 | 395 Pages | ISBN: 1441908013 | PDF | 11 MB Clinical PET and PET/CT, 2nd Edition presents a valuable overview of the basic principles and clinical applications of PET and PET/CT. Emphasis is placed on the familiarization of normal distribution, artifacts, and common imaging agents such as FDG in conjunction with CT, MRI, and US to establish the clinical effectiveness of PET and PET/CT.

iDoctus BioMedLib™ IHS - International Headache Society» Home Scienty Scienty es un motor de búsqueda web creado por NeoScientia.com. Scienty hace uso de la aplicación Google Custom Search Engine para optimizar los resultados de búsqueda recuperados por Google ante una consulta, y mostrarte aquellos más relacionados con el sector científico, académico, y universitario. Concretamente, da prioridad a aquellos sitios web que alberguen en un mayor promedio las siguientes palabras clave en sus metadatos y contenidos (título, descripción, texto, URL, enlaces internos…): Palabras clave priorizadas: scientist, academia, university, scientific, science, ciencia, cientifico, research, researcher, article, paper, universidad, investigación, investigador, phd, doctorado, master, máster, undergraduate, pregrado, postgraduate, posgrado, thesis, tesis, educación, edu, education, divulgación, communication, dissertation, postdoctoral, posdoctoral, professor, PhD, Ph.D, carrera Guías para la inclusión de sitios web:

Quertle To find the most focused results, Quertle searches for assertions made by the author(s) that tie all of your search terms together in a meaningful way. Thus, it is best to focus your initial query on the core concepts of interest, such as "what causes B". Then, add additional terms, such as "mice", and dates when you filter the results. Authors and journals should be entered into their own search boxes. Example use this: caffeine treats migraines instead of this: caffeine treats migraines in mice 2009 Smith As you type, automatic suggestions will appear. Start typing a name to display a list of authors. Separate multiple authors by a comma. Start typing to display a list of journals. Separate multiple journals by a comma. This tab displays documents where the author(s) made a statement connecting your search terms together in a meaningful way. As you filter the results, the number will update. To remove any filter, click its When multiple filters are applied, all can be removed using the

Fisterra PubViz In short, PubViz is developed to provide the capability of utilizing external knowledge as well as interactive visual query functions for more efficient exploration of the Medline database. The current version has the ability to utilize protein-protein interaction data during Medline search and enable researchers to identify functionally related Medline records not retrievable in existing search engines. It can also utilize the structure relationship of different type of genetic markers including cytobands, microsatellite/STS markers, SNPs and genes derived from human genome assembly and HapMap data for deep search of genetically related Medline records. (Please note: PubViz is currently development.

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