Base de dados : MEDLINE
Pesquisa : L01.178.682.192.836.285.490 [Categoria DeCS]
Referências encontradas : 46 [refinar]
Mostrando: 1 .. 10   no formato [Detalhado]

página 1 de 5 ir para página              

  1 / 46 MEDLINE  
              next record last record
seleciona
para imprimir
Fotocópia
PubMed Central Texto completo
Texto completo
[PMID]:25821813
[Au] Autor:Huang G; Lu Y; Lu C; Zheng M; Cai YD
[Ad] Endereço:Institute of Systems Biology, Shanghai University, Shanghai 200444, China ; Department of Mathematics, Shaoyang University, Shaoyang, Hunan 422000, China.
[Ti] Título:Prediction of drug indications based on chemical interactions and chemical similarities.
[So] Source:Biomed Res Int;2015:584546, 2015.
[Is] ISSN:2314-6141
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Discovering potential indications of novel or approved drugs is a key step in drug development. Previous computational approaches could be categorized into disease-centric and drug-centric based on the starting point of the issues or small-scaled application and large-scale application according to the diversity of the datasets. Here, a classifier has been constructed to predict the indications of a drug based on the assumption that interactive/associated drugs or drugs with similar structures are more likely to target the same diseases using a large drug indication dataset. To examine the classifier, it was conducted on a dataset with 1,573 drugs retrieved from Comprehensive Medicinal Chemistry database for five times, evaluated by 5-fold cross-validation, yielding five 1st order prediction accuracies that were all approximately 51.48%. Meanwhile, the model yielded an accuracy rate of 50.00% for the 1st order prediction by independent test on a dataset with 32 other drugs in which drug repositioning has been confirmed. Interestingly, some clinically repurposed drug indications that were not included in the datasets are successfully identified by our method. These results suggest that our method may become a useful tool to associate novel molecules with new indications or alternative indications with existing drugs.
[Mh] Termos MeSH primário: Algoritmos
Mineração de Dados/métodos
Bases de Dados de Produtos Farmacêuticos
Desenho de Drogas
Interações Medicamentosas
Reposicionamento de Medicamentos/métodos
[Mh] Termos MeSH secundário: Dicionários Farmacêuticos como Assunto
[Pt] Tipo de publicação:JOURNAL ARTICLE; RESEARCH SUPPORT, NON-U.S. GOV'T
[Em] Mês de entrada:1512
[Cu] Atualização por classe:171116
[Lr] Data última revisão:
171116
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:150331
[St] Status:MEDLINE
[do] DOI:10.1155/2015/584546


  2 / 46 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
[PMID]:25160352
[Au] Autor:Patapovas A; Pfistermeister B; Tarkhov A; Terfloth L; Maas R; Fromm MF; Kornhuber J; Prokosch HU; Bürkle T
[Ad] Endereço:Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany.
[Ti] Título:The effect object paradigm--a means to support medication safety with clinical decision support.
[So] Source:Stud Health Technol Inform;205:1065-9, 2014.
[Is] ISSN:0926-9630
[Cp] País de publicação:Netherlands
[La] Idioma:eng
[Ab] Resumo:BACKGROUND: In many countries, officially approved drug information known as summary of product characteristics (SPC) is mostly available in text form, which cannot be used for Clinical Decision Support Systems (CDSS). It may be essential however to substantiate CDSS advice with such legally binding text snippets. In an attempt to link various drug data sources including SPC towards a CDSS to support medication safety in psychiatric patients we arrived at the notion of an effect object. METHODS: A requirements analysis revealed data items and data structure which are needed from the patient and from the drug information source for the CDSS functionality. Published drug data modelling approaches were analyzed and found unsuitable. A conceptional database modeling approach using top down and bottom up modeling was performed. RESULTS: The schema based data model implemented within the django framework centered on SPC "effect objects" which comprise all SPC data required for the respective CDSS function such as search for contraindications in the proposed medication. Today six effect objects have been defined for contraindications and warnings, missing indications, adverse effects, drug-drug interactions, dosing and pharmacokinetics. CONCLUSION: The transformation of SPC data to a database-driven "effect objects" structure permits decoupling between the CDSS functions and different underlying data sources and supports the design of reusable, stable and verified CDSS functions.
[Mh] Termos MeSH primário: Sistemas de Notificação de Reações Adversas a Medicamentos/organização & administração
Algoritmos
Sistemas de Informação em Farmácia Clínica/organização & administração
Sistemas de Apoio a Decisões Clínicas/organização & administração
Dicionários Farmacêuticos como Assunto
Armazenamento e Recuperação da Informação/métodos
Sistemas de Medicação no Hospital/organização & administração
[Mh] Termos MeSH secundário: Inteligência Artificial
Alemanha
Processamento de Linguagem Natural
Farmacovigilância
Vocabulário Controlado
[Pt] Tipo de publicação:JOURNAL ARTICLE; RESEARCH SUPPORT, NON-U.S. GOV'T
[Em] Mês de entrada:1505
[Cu] Atualização por classe:171116
[Lr] Data última revisão:
171116
[Sb] Subgrupo de revista:T
[Da] Data de entrada para processamento:140828
[St] Status:MEDLINE


  3 / 46 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
[PMID]:25160341
[Au] Autor:Declerck G; Souvignet J; Rodrigues JM; Jaulent MC
[Ad] Endereço:INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France.
[Ti] Título:Automatic annotation of ICD-to-MedDRA mappings with SKOS predicates.
[So] Source:Stud Health Technol Inform;205:1013-7, 2014.
[Is] ISSN:0926-9630
[Cp] País de publicação:Netherlands
[La] Idioma:eng
[Ab] Resumo:Robust alignments between ICD and MedDRA are essential to enable the secondary use of clinical data for pharmacovigilance research. UMLS makes available ICD-to-MedDRA mappings, but they are only poorly specified, which introduces difficulties when exploited in an automatic way. SKOS vocabulary can help achieve quality and machine-processable mappings. We have developed an algorithm based on several simple rules which annotates automatically ICD-to-MedDRA mappings with SKOS predicates. The method was tested and evaluated on a sample of ICD-10-to MedDRA mappings extracted from UMLS. The algorithm demonstrated satisfying performances, especially for skos:exactMatch properties, which suggests that automatic methods can be used to improve the quality of terminology mappings.
[Mh] Termos MeSH primário: Sistemas de Notificação de Reações Adversas a Medicamentos/organização & administração
Dicionários Farmacêuticos como Assunto
Guias como Assunto
Classificação Internacional de Doenças/normas
Processamento de Linguagem Natural
Terminologia como Assunto
Vocabulário Controlado
[Mh] Termos MeSH secundário: Algoritmos
Inteligência Artificial
Documentação/normas
Farmacovigilância
Semântica
[Pt] Tipo de publicação:JOURNAL ARTICLE; RESEARCH SUPPORT, NON-U.S. GOV'T
[Em] Mês de entrada:1505
[Cu] Atualização por classe:171116
[Lr] Data última revisão:
171116
[Sb] Subgrupo de revista:T
[Da] Data de entrada para processamento:140828
[St] Status:MEDLINE


  4 / 46 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
Texto completo
[PMID]:24492783
[Au] Autor:Chen L; Lu J; Zhang N; Huang T; Cai YD
[Ad] Endereço:College of Information Engineering, Shanghai Maritime University, Shanghai 201306, People's Republic of China. chen_lei1@163.com.
[Ti] Título:A hybrid method for prediction and repositioning of drug Anatomical Therapeutic Chemical classes.
[So] Source:Mol Biosyst;10(4):868-77, 2014 Apr.
[Is] ISSN:1742-2051
[Cp] País de publicação:England
[La] Idioma:eng
[Ab] Resumo:In the Anatomical Therapeutic Chemical (ATC) classification system, therapeutic drugs are divided into 14 main classes according to the organ or system on which they act and their chemical, pharmacological and therapeutic properties. This system, recommended by the World Health Organization (WHO), provides a global standard for classifying medical substances and serves as a tool for international drug utilization research to improve quality of drug use. In view of this, it is necessary to develop effective computational prediction methods to identify the ATC-class of a given drug, which thereby could facilitate further analysis of this system. In this study, we initiated an attempt to develop a prediction method and to gain insights from it by utilizing ontology information of drug compounds. Since only about one-fourth of drugs in the ATC classification system have ontology information, a hybrid prediction method combining the ontology information, chemical interaction information and chemical structure information of drug compounds was proposed for the prediction of drug ATC-classes. As a result, by using the Jackknife test, the 1st prediction accuracies for identifying the 14 main ATC-classes in the training dataset, the internal validation dataset and the external validation dataset were 75.90%, 75.70% and 66.36%, respectively. Analysis of some samples with false-positive predictions in the internal and external validation datasets indicated that some of them may even have a relationship with the false-positive predicted ATC-class, suggesting novel uses of these drugs. It was conceivable that the proposed method could be used as an efficient tool to identify ATC-classes of novel drugs or to discover novel uses of known drugs.
[Mh] Termos MeSH primário: Química Farmacêutica
Bases de Dados de Produtos Farmacêuticos
Dicionários Farmacêuticos como Assunto
[Mh] Termos MeSH secundário: Catálogos de Medicamentos
Bases de Dados de Compostos Químicos
Uso de Medicamentos
Seres Humanos
[Pt] Tipo de publicação:JOURNAL ARTICLE; RESEARCH SUPPORT, NON-U.S. GOV'T
[Em] Mês de entrada:1412
[Cu] Atualização por classe:171116
[Lr] Data última revisão:
171116
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:140205
[St] Status:MEDLINE
[do] DOI:10.1039/c3mb70490d


  5 / 46 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
PubMed Central Texto completo
[PMID]:23920673
[Au] Autor:Winnenburg R; Bodenreider O
[Ad] Endereço:National Library of Medicine, Maryland, MD, USA.
[Ti] Título:Exploring pharmacoepidemiologic groupings of drugs from a clinical perspective.
[So] Source:Stud Health Technol Inform;192:827-31, 2013.
[Is] ISSN:0926-9630
[Cp] País de publicação:Netherlands
[La] Idioma:eng
[Ab] Resumo:OBJECTIVES: To investigate the extent to which pharmacoepidemiologic groupings are homogeneous in terms of clinical properties. METHODS: In our analysis, we classified drug subgroups from the pharmacoepidemiologic Anatomical Therapeutic Chemical (ATC) classification system based on clinical drug properties. We established mappings from ATC fifth level drug entities to drug property annotations in the National Drug File Reference Terminology (NDF-RT), including therapeutic categories, mechanisms of action, and physiologic effects. Based on the annotations for the individual drugs we computed homogeneity scores for all ATC groups and analyzed their distribution. CONCLUSIONS: We found ATC groups to be generally homogeneous, more so for mechanisms of action, and physiologic effects than for therapeutic intent. However, only half of all ATC drugs can be analyzed with this approach, in part because of missing properties in NDF-RT.
[Mh] Termos MeSH primário: Bases de Dados de Produtos Farmacêuticos
Dicionários Farmacêuticos como Assunto
Processamento de Linguagem Natural
Preparações Farmacêuticas/classificação
Farmacoepidemiologia/métodos
Terminologia como Assunto
Vocabulário Controlado
[Pt] Tipo de publicação:JOURNAL ARTICLE; RESEARCH SUPPORT, N.I.H., INTRAMURAL
[Nm] Nome de substância:
0 (Pharmaceutical Preparations)
[Em] Mês de entrada:1504
[Cu] Atualização por classe:171116
[Lr] Data última revisão:
171116
[Sb] Subgrupo de revista:T
[Da] Data de entrada para processamento:130808
[St] Status:MEDLINE


  6 / 46 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
Texto completo
[PMID]:23743691
[Au] Autor:Haddad C; Sidoroff A; Kardaun SH; Mockenhaupt M; Creamer D; Dunant A; Roujeau JC
[Ad] Endereço:Henri Mondor Hospital, University Paris-Est Créteil, Créteil, France.
[Ti] Título:Stevens-Johnson syndrome/toxic epidermal necrolysis: are drug dictionaries correctly informing physicians regarding the risk?
[So] Source:Drug Saf;36(8):681-6, 2013 Aug.
[Is] ISSN:1179-1942
[Cp] País de publicação:New Zealand
[La] Idioma:eng
[Ab] Resumo:BACKGROUND: Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN) are severe drug reactions associated with high mortality and multiple incapacitating sequelae. In the past 20 years, two large multinational case control studies, published in 1995 and 2008, had identified different degrees of drug association with SJS/TEN: 'strongly associated', 'associated', 'suspected' and 'not suspected' medications. OBJECTIVE: The aim of this study was to check the adequacy of mention of risk of SJS/TEN in the drug dictionaries most widely used by physicians in five European countries. STUDY DESIGN: In each country one expert investigator looked at the most widely used drug dictionary (2009 edition) for mentions of risk of SJS/TEN. This was done for a predefined list of medications with a different degree of risk. The presence and clarity or absence of warning was compared with available evidence provided by published results from case-control studies. SETTING: The five countries participating in the RegiSCAR group: Austria, France, Germany, The Netherlands and the UK. RESULTS: A total of 3,268 drug descriptions of medications for systemic use were analysed, including all brands of 14 'strongly associated' drugs, 5 'associated' drugs and 12 widely used drugs with no established association. Discrepancies were found by country, and between descriptions for different brands of the same generic. Among 522 descriptions of 14 'strongly associated' drugs, only 5 did not mention the risk. For the 1,013 descriptions of 'associated' drugs, 3 % did not mention the risk. One-third of 'not suspected' drugs contained a specific or less specific warning (e.g. bullous cutaneous eruption). Warnings for 'strongly associated' medications were often as imprecise as those for 'not suspected' drugs. CONCLUSION: Information on the risk of SJS/TEN in drug dictionaries needs improvement to enhance the quality of advice given by general physicians and to raise the understanding of risk by patients.
[Mh] Termos MeSH primário: Competência Clínica
Dicionários Farmacêuticos como Assunto
Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/mortalidade
Médicos
Risco
Síndrome de Stevens-Johnson/mortalidade
[Mh] Termos MeSH secundário: Estudos de Casos e Controles
Europa (Continente)
Educação em Saúde/normas
Seres Humanos
[Pt] Tipo de publicação:EVALUATION STUDIES; JOURNAL ARTICLE; RESEARCH SUPPORT, NON-U.S. GOV'T
[Em] Mês de entrada:1410
[Cu] Atualização por classe:171116
[Lr] Data última revisão:
171116
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:130608
[St] Status:MEDLINE
[do] DOI:10.1007/s40264-013-0070-6


  7 / 46 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
PubMed Central Texto completo
Texto completo
[PMID]:22643058
[Au] Autor:Marian AA; Dexter F; Tucker P; Todd MM
[Ad] Endereço:Department of Anesthesia, University of Iowa, Iowa City, IA 52242, USA. anil-marian@uiowa.edu
[Ti] Título:Comparison of alphabetical versus categorical display format for medication order entry in a simulated touch screen anesthesia information management system: an experiment in clinician-computer interaction in anesthesia.
[So] Source:BMC Med Inform Decis Mak;12:46, 2012 May 29.
[Is] ISSN:1472-6947
[Cp] País de publicação:England
[La] Idioma:eng
[Ab] Resumo:BACKGROUND: Anesthesia information management system (AIMS) records should be designed and configured to facilitate the accurate and prompt recording of multiple drugs administered coincidentally or in rapid succession. METHODS: We proposed two touch-screen display formats for use with our department's new EPIC touch-screen AIMS. In one format, medication "buttons" were arranged in alphabetical order (i.e. A-C, D-H etc.). In the other, buttons were arranged in categories (Common, Fluids, Cardiovascular, Coagulation etc.). Both formats were modeled on an iPad screen to resemble the AIMS interface. Anesthesia residents, anesthesiologists, and Certified Registered Nurse Anesthetists (n = 60) were then asked to find and touch the correct buttons for a series of medications whose names were displayed to the side of the entry screen. The number of entries made within 2 minutes was recorded. This was done 3 times for each format, with the 1st format chosen randomly. Data were analyzed from the third trials with each format to minimize differences in learning. RESULTS: The categorical format had a mean of 5.6 more drugs entered using the categorical method in two minutes than the alphabetical format (95% confidence interval [CI] 4.5 to 6.8, P < 0.0001). The findings were the same regardless of the order of testing (i.e. alphabetical-categorical vs. categorical - alphabetical) and participants' years of clinical experience. Most anesthesia providers made no (0) errors for most trials (N = 96/120 trials, lower 95% limit 73%, P < 0.0001). There was no difference in error rates between the two formats (P = 0.53). CONCLUSIONS: The use of touch-screen user interfaces in healthcare is increasingly common. Arrangement of drugs names in a categorical display format in the medication order-entry touch screen of an AIMS can result in faster data entry compared to an alphabetical arrangement of drugs. Results of this quality improvement project were used in our department's design of our final intraoperative electronic anesthesia record. This testing approach using cognitive and usability engineering methods can be used to objectively design and evaluate many aspects of the clinician-computer interaction in electronic health records.
[Mh] Termos MeSH primário: Anestesiologia/instrumentação
Terminais de Computador
Computadores de Mão/utilização
Dicionários Farmacêuticos como Assunto
Sistemas de Registro de Ordens Médicas
Interface Usuário-Computador
[Mh] Termos MeSH secundário: Anestesiologia/recursos humanos
Anestesiologia/normas
Protocolos Clínicos
Sistemas de Apoio a Decisões Clínicas/organização & administração
Seres Humanos
Internet
Sistemas de Registro de Ordens Médicas/estatística & dados numéricos
Erros de Medicação/prevenção & controle
Erros de Medicação/psicologia
Erros de Medicação/estatística & dados numéricos
Linguagens de Programação
Melhoria de Qualidade/normas
Estatísticas não Paramétricas
Estudos de Tempo e Movimento
Simplificação do Trabalho
[Pt] Tipo de publicação:COMPARATIVE STUDY; JOURNAL ARTICLE
[Em] Mês de entrada:1210
[Cu] Atualização por classe:171116
[Lr] Data última revisão:
171116
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:120531
[St] Status:MEDLINE
[do] DOI:10.1186/1472-6947-12-46


  8 / 46 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
Texto completo
[PMID]:22142948
[Au] Autor:Zhou L; Plasek JM; Mahoney LM; Chang FY; DiMaggio D; Rocha RA
[Ad] Endereço:Clinical Informatics Research & Development, Partners HealthCare System, Inc., Wellesley, USA. Lzhou2@partners.org
[Ti] Título:Mapping Partners Master Drug Dictionary to RxNorm using an NLP-based approach.
[So] Source:J Biomed Inform;45(4):626-33, 2012 Aug.
[Is] ISSN:1532-0480
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:OBJECTIVE: To develop an automated method based on natural language processing (NLP) to facilitate the creation and maintenance of a mapping between RxNorm and a local medication terminology for interoperability and meaningful use purposes. METHODS: We mapped 5961 terms from Partners Master Drug Dictionary (MDD) and 99 of the top prescribed medications to RxNorm. The mapping was conducted at both term and concept levels using an NLP tool, called MTERMS, followed by a manual review conducted by domain experts who created a gold standard mapping. The gold standard was used to assess the overall mapping between MDD and RxNorm and evaluate the performance of MTERMS. RESULTS: Overall, 74.7% of MDD terms and 82.8% of the top 99 terms had an exact semantic match to RxNorm. Compared to the gold standard, MTERMS achieved a precision of 99.8% and a recall of 73.9% when mapping all MDD terms, and a precision of 100% and a recall of 72.6% when mapping the top prescribed medications. CONCLUSION: The challenges and gaps in mapping MDD to RxNorm are mainly due to unique user or application requirements for representing drug concepts and the different modeling approaches inherent in the two terminologies. An automated approach based on NLP followed by human expert review is an efficient and feasible way for conducting dynamic mapping.
[Mh] Termos MeSH primário: Dicionários Farmacêuticos como Assunto
Informática Médica/métodos
Informática Médica/normas
Processamento de Linguagem Natural
Preparações Farmacêuticas/classificação
RxNorm
Vocabulário Controlado
[Mh] Termos MeSH secundário: Seres Humanos
[Pt] Tipo de publicação:JOURNAL ARTICLE; RESEARCH SUPPORT, NON-U.S. GOV'T; RESEARCH SUPPORT, U.S. GOV'T, P.H.S.
[Nm] Nome de substância:
0 (Pharmaceutical Preparations)
[Em] Mês de entrada:1303
[Cu] Atualização por classe:171116
[Lr] Data última revisão:
171116
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:111207
[St] Status:MEDLINE
[do] DOI:10.1016/j.jbi.2011.11.006


  9 / 46 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
[PMID]:22230935
[Au] Autor:Arita M; Yoshimoto M; Suwa K; Hirai A; Kanaya S; Shibahara N; Tanaka K
[Ad] Endereço:Department of Biophysics and Biochemistry, Graduate School of Science, The University of Tokyo, Bunkyo-ku, Tokyo, Japan. arita@bi.s.u-tokyo.ac.jp
[Ti] Título:Database for crude drugs and Kampo medicine.
[So] Source:Genome Inform;25(1):1-11, 2011.
[Is] ISSN:0919-9454
[Cp] País de publicação:Japan
[La] Idioma:eng
[Ab] Resumo:A wiki-based repository for crude drugs and Kampo medicine is introduced. It provides taxonomic and chemical information for 158 crude drugs and 348 prescriptions of the traditional Kampo medicine in Japan, which is a variation of ancient Chinese medicine. The system is built on MediaWiki with extensions for inline page search and for sending user-input elements to the server. These functions together realize implementation of word checks and data integration at the user-level. In this scheme, any user can participate in creating an integrated database with controlled vocabularies on the wiki system. Our implementation and data are accessible at http://metabolomics.jp/wiki/.
[Mh] Termos MeSH primário: Bases de Dados de Produtos Farmacêuticos
Medicamentos de Ervas Chinesas/química
Medicina Kampo
[Mh] Termos MeSH secundário: Misturas Complexas/química
Dicionários Farmacêuticos como Assunto
Combinação de Medicamentos
Software
[Pt] Tipo de publicação:JOURNAL ARTICLE; RESEARCH SUPPORT, NON-U.S. GOV'T
[Nm] Nome de substância:
0 (Complex Mixtures); 0 (Drug Combinations); 0 (Drugs, Chinese Herbal)
[Em] Mês de entrada:1312
[Cu] Atualização por classe:171116
[Lr] Data última revisão:
171116
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:120111
[St] Status:MEDLINE


  10 / 46 MEDLINE  
              first record previous record
seleciona
para imprimir
Fotocópia
Texto completo
[PMID]:22170948
[Au] Autor:Goldenholz DM
[Ad] Endereço:Department of Neurology, UC Davis Medical Center, 4860 Y Street, Suite 3700, Sacramento, CA 95817, USA. Goldenholz@alum.bu.edu
[Ti] Título:Media and book reviews: Medications: how can we know them all?
[So] Source:Neurology;77(24):e143-4, 2011 Dec 13.
[Is] ISSN:1526-632X
[Cp] País de publicação:United States
[La] Idioma:eng
[Mh] Termos MeSH primário: Computadores de Mão
Dicionários Farmacêuticos como Assunto
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1202
[Cu] Atualização por classe:171116
[Lr] Data última revisão:
171116
[Sb] Subgrupo de revista:AIM; IM
[Da] Data de entrada para processamento:111216
[St] Status:MEDLINE
[do] DOI:10.1212/WNL.0b013e31823d76ca



página 1 de 5 ir para página              
   


Refinar a pesquisa
  Base de dados : MEDLINE Formulário avançado   

    Pesquisar no campo  
1  
2
3
 
           



Search engine: iAH v2.6 powered by WWWISIS

BIREME/OPAS/OMS - Centro Latino-Americano e do Caribe de Informação em Ciências da Saúde