Base de dados : MEDLINE
Pesquisa : L01.906.893 [Categoria DeCS]
Referências encontradas : 2506 [refinar]
Mostrando: 1 .. 10   no formato [Detalhado]

página 1 de 251 ir para página                         

  1 / 2506 MEDLINE  
              next record last record
seleciona
para imprimir
Fotocópia
Texto completo
[PMID]:29385199
[Au] Autor:Schaefer C; Mallela N; Seggewiß J; Lechtape B; Omran H; Dirksen U; Korsching E; Potratz J
[Ad] Endereço:Pediatric Hematology and Oncology, University Hospital Münster, Münster, Germany.
[Ti] Título:Target discovery screens using pooled shRNA libraries and next-generation sequencing: A model workflow and analytical algorithm.
[So] Source:PLoS One;13(1):e0191570, 2018.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:In the search for novel therapeutic targets, RNA interference screening has become a valuable tool. High-throughput technologies are now broadly accessible but their assay development from baseline remains resource-intensive and challenging. Focusing on this assay development process, we here describe a target discovery screen using pooled shRNA libraries and next-generation sequencing (NGS) deconvolution in a cell line model of Ewing sarcoma. In a strategy designed for comparative and synthetic lethal studies, we screened for targets specific to the A673 Ewing sarcoma cell line. Methods, results and pitfalls are described for the entire multi-step screening procedure, from lentiviral shRNA delivery to bioinformatics analysis, illustrating a complete model workflow. We demonstrate that successful studies are feasible from the first assay performance and independent of specialized screening units. Furthermore, we show that a resource-saving screen depth of 100-fold average shRNA representation can suffice to generate reproducible target hits despite heterogeneity in the derived datasets. Because statistical analysis methods are debatable for such datasets, we created ProFED, an analysis package designed to facilitate descriptive data analysis and hit calling using an aim-oriented profile filtering approach. In its versatile design, this open-source online tool provides fast and easy analysis of shRNA and other count-based datasets to complement other analytical algorithms.
[Mh] Termos MeSH primário: Descoberta de Drogas/métodos
Avaliação Pré-Clínica de Medicamentos/métodos
Biblioteca Gênica
RNA Interferente Pequeno/genética
[Mh] Termos MeSH secundário: Algoritmos
Linhagem Celular Tumoral
Biologia Computacional
Células HEK293
Sequenciamento de Nucleotídeos em Larga Escala
Seres Humanos
Lentivirus/genética
Interferência de RNA
Sarcoma de Ewing/tratamento farmacológico
Sarcoma de Ewing/genética
Análise de Sequência de RNA
Fluxo de Trabalho
[Pt] Tipo de publicação:JOURNAL ARTICLE; RESEARCH SUPPORT, NON-U.S. GOV'T
[Nm] Nome de substância:
0 (RNA, Small Interfering)
[Em] Mês de entrada:1803
[Cu] Atualização por classe:180302
[Lr] Data última revisão:
180302
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:180201
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0191570


  2 / 2506 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
Texto completo
[PMID]:29352322
[Au] Autor:Mohr C; Friedrich A; Wojnar D; Kenar E; Polatkan AC; Codrea MC; Czemmel S; Kohlbacher O; Nahnsen S
[Ad] Endereço:Applied Bioinformatics, Center for Bioinformatics Tübingen, University of Tübingen, Sand 14, 72076 Tübingen, Germany.
[Ti] Título:qPortal: A platform for data-driven biomedical research.
[So] Source:PLoS One;13(1):e0191603, 2018.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Modern biomedical research aims at drawing biological conclusions from large, highly complex biological datasets. It has become common practice to make extensive use of high-throughput technologies that produce big amounts of heterogeneous data. In addition to the ever-improving accuracy, methods are getting faster and cheaper, resulting in a steadily increasing need for scalable data management and easily accessible means of analysis. We present qPortal, a platform providing users with an intuitive way to manage and analyze quantitative biological data. The backend leverages a variety of concepts and technologies, such as relational databases, data stores, data models and means of data transfer, as well as front-end solutions to give users access to data management and easy-to-use analysis options. Users are empowered to conduct their experiments from the experimental design to the visualization of their results through the platform. Here, we illustrate the feature-rich portal by simulating a biomedical study based on publically available data. We demonstrate the software's strength in supporting the entire project life cycle. The software supports the project design and registration, empowers users to do all-digital project management and finally provides means to perform analysis. We compare our approach to Galaxy, one of the most widely used scientific workflow and analysis platforms in computational biology. Application of both systems to a small case study shows the differences between a data-driven approach (qPortal) and a workflow-driven approach (Galaxy). qPortal, a one-stop-shop solution for biomedical projects offers up-to-date analysis pipelines, quality control workflows, and visualization tools. Through intensive user interactions, appropriate data models have been developed. These models build the foundation of our biological data management system and provide possibilities to annotate data, query metadata for statistics and future re-analysis on high-performance computing systems via coupling of workflow management systems. Integration of project and data management as well as workflow resources in one place present clear advantages over existing solutions.
[Mh] Termos MeSH primário: Pesquisa Biomédica
Metodologias Computacionais
Software
[Mh] Termos MeSH secundário: Pesquisa Biomédica/estatística & dados numéricos
Biologia Computacional/métodos
Biologia Computacional/estatística & dados numéricos
Sistemas de Gerenciamento de Base de Dados/estatística & dados numéricos
Bases de Dados Factuais/estatística & dados numéricos
Bases de Dados Genéticas/estatística & dados numéricos
Sequenciamento de Nucleotídeos em Larga Escala/estatística & dados numéricos
Seres Humanos
Internet
Interface Usuário-Computador
Fluxo de Trabalho
[Pt] Tipo de publicação:JOURNAL ARTICLE; RESEARCH SUPPORT, NON-U.S. GOV'T
[Em] Mês de entrada:1802
[Cu] Atualização por classe:180226
[Lr] Data última revisão:
180226
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:180121
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0191603


  3 / 2506 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
Texto completo
[PMID]:28470618
[Au] Autor:Black C; Barker JJ; Hitchman RB; Kwong HS; Festenstein S; Acton TB
[Ad] Endereço:Evotec Ltd, 114 Innovation Drive, Milton Park, Abingdon, Oxfordshire, OX14 4RZ, UK.
[Ti] Título:High-Throughput Production of Proteins in E. coli for Structural Studies.
[So] Source:Methods Mol Biol;1586:359-371, 2017.
[Is] ISSN:1940-6029
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:We have developed a standardized and efficient workflow for high-throughput (HT) protein expression in E. coli and parallel purification which can be tailored to the downstream application of the target proteins. It includes a one-step purification for the purposes of functional assays and a two-step protocol for crystallographic studies, with the option of on-column tag removal.
[Mh] Termos MeSH primário: Clonagem Molecular/métodos
Escherichia coli/genética
Proteínas Recombinantes/genética
[Mh] Termos MeSH secundário: Animais
Eletroforese em Gel de Poliacrilamida/métodos
Ensaios de Triagem em Larga Escala/economia
Ensaios de Triagem em Larga Escala/métodos
Seres Humanos
Conformação Proteica
Proteômica/métodos
Proteínas Recombinantes/química
Proteínas Recombinantes/isolamento & purificação
Transformação Genética
Fluxo de Trabalho
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Nm] Nome de substância:
0 (Recombinant Proteins)
[Em] Mês de entrada:1802
[Cu] Atualização por classe:180220
[Lr] Data última revisão:
180220
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170505
[St] Status:MEDLINE
[do] DOI:10.1007/978-1-4939-6887-9_24


  4 / 2506 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
[PMID]:27778059
[Au] Autor:Kenngott HG; Wagner M; Preukschas AA; Müller-Stich BP
[Ad] Endereço:Abteilung für Allgemein-, Viszeral- und Transplantationschirurgie, Klinikum der Universität Heidelberg, Chirurgische Universitätsklinik, Universität Heidelberg, Im Neuenheimer Feld 110, 69120, Heidelberg, Deutschland.
[Ti] Título:[Intelligent operating room suite : From passive medical devices to the self-thinking cognitive surgical assistant].
[Ti] Título:Der intelligente Operationssaal : Vom passiven Gerätepark zum mitdenkenden, kognitiven Assistenten..
[So] Source:Chirurg;87(12):1033-1038, 2016 Dec.
[Is] ISSN:1433-0385
[Cp] País de publicação:Germany
[La] Idioma:ger
[Ab] Resumo:Modern operating room (OR) suites are mostly digitally connected but until now the primary focus was on the presentation, transfer and distribution of images. Device information and processes within the operating theaters are barely considered. Cognitive assistance systems have triggered a fundamental rethinking in the automotive industry as well as in logistics. In principle, tasks in the OR, some of which are highly repetitive, also have great potential to be supported by automated cognitive assistance via a self-thinking system. This includes the coordination of the entire workflow in the perioperative process in both the operating theater and the whole hospital. With corresponding data from hospital information systems, medical devices and appropriate models of the surgical process, intelligent systems could optimize the workflow in the operating theater in the near future and support the surgeon. Preliminary results on the use of device information and automatically controlled OR suites are already available. Such systems include, for example the guidance of laparoscopic camera systems. Nevertheless, cognitive assistance systems that make use of knowledge about patients, processes and other pieces of information to improve surgical treatment are not yet available in the clinical routine but are urgently needed in order to automatically assist the surgeon in situation-related activities and thus substantially improve patient care.
[Mh] Termos MeSH primário: Salas Cirúrgicas/métodos
Salas Cirúrgicas/organização & administração
[Mh] Termos MeSH secundário: Processamento Automatizado de Dados/métodos
Processamento Automatizado de Dados/organização & administração
Seres Humanos
Laparoscopia/instrumentação
Laparoscopia/métodos
Monitorização Intraoperatória/instrumentação
Monitorização Intraoperatória/métodos
Sistemas de Informação em Salas Cirúrgicas/organização & administração
Software
Cirurgia Assistida por Computador/instrumentação
Cirurgia Assistida por Computador/métodos
Equipamentos Cirúrgicos/normas
Fluxo de Trabalho
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1802
[Cu] Atualização por classe:180201
[Lr] Data última revisão:
180201
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:161026
[St] Status:MEDLINE


  5 / 2506 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
Texto completo
[PMID]:27770852
[Au] Autor:Misyura M; Zhang T; Sukhai MA; Thomas M; Garg S; Kamel-Reid S; Stockley TL
[Ad] Endereço:Advanced Molecular Diagnostics Laboratory, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
[Ti] Título:Comparison of Next-Generation Sequencing Panels and Platforms for Detection and Verification of Somatic Tumor Variants for Clinical Diagnostics.
[So] Source:J Mol Diagn;18(6):842-850, 2016 11.
[Is] ISSN:1943-7811
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Use of next-generation sequencing to detect somatic variants in DNA extracted from formalin-fixed, paraffin-embedded tumor tissues poses a challenge for clinical molecular diagnostic laboratories because of variable DNA quality and quantity, and the potential to detect low allele frequency somatic variants difficult to verify by non-next-generation sequencing methods. We evaluated somatic variant detection performance of the MiSeq and Ion Proton benchtop sequencers using two commercially available panels, the TruSeq Amplicon Cancer Panel and the AmpliSeq Cancer Hotspot Panel Version 2. Both the MiSeq-TruSeq Amplicon Cancer Panel and Ion Proton-AmpliSeq Cancer Hotspot Panel Version 2 were comparable in terms of detection of somatic variants and allele frequency determination using DNA extracted from tumor tissue. Concordance was 100% between the panels for detection of somatic variants in genomic regions tested by both panels, including 27 variants present at low somatic allele frequency (<15%). Use of both the MiSeq and Ion Proton platforms in a combined workflow enabled detection of potentially actionable variants with importance for patient diagnosis, prognosis, or treatment in 49% (305/621) of cases. Overall, a combined workflow using both platforms enabled successful molecular profiling of 96% (621/644) of tumor samples, and provided an approach for verification of somatic variants not amenable to verification by Sanger sequencing (<15% variant allele frequency).
[Mh] Termos MeSH primário: Testes Genéticos
Variação Genética
Sequenciamento de Nucleotídeos em Larga Escala
Neoplasias/diagnóstico
Neoplasias/genética
[Mh] Termos MeSH secundário: Alelos
Biomarcadores Tumorais
Frequência do Gene
Testes Genéticos/métodos
Testes Genéticos/normas
Sequenciamento de Nucleotídeos em Larga Escala/métodos
Sequenciamento de Nucleotídeos em Larga Escala/normas
Seres Humanos
Reprodutibilidade dos Testes
Sensibilidade e Especificidade
Fluxo de Trabalho
[Pt] Tipo de publicação:COMPARATIVE STUDY; JOURNAL ARTICLE; RESEARCH SUPPORT, NON-U.S. GOV'T
[Nm] Nome de substância:
0 (Biomarkers, Tumor)
[Em] Mês de entrada:1706
[Cu] Atualização por classe:180122
[Lr] Data última revisão:
180122
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:161025
[St] Status:MEDLINE


  6 / 2506 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
Texto completo
[PMID]:28748430
[Au] Autor:Singh H; Yadav G; Mallaiah R; Joshi P; Joshi V; Kaur R; Bansal S; Brahmachari SK
[Ad] Endereço:Academy of Scientific and Innovative Research, New Delhi, India. harpreet_singh@oxyent.com.
[Ti] Título:iNICU - Integrated Neonatal Care Unit: Capturing Neonatal Journey in an Intelligent Data Way.
[So] Source:J Med Syst;41(8):132, 2017 Aug.
[Is] ISSN:1573-689X
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Neonatal period represents first 28 days of life, which is the most vulnerable time for a child's survival especially for the preterm babies. High neonatal mortality is a prominent and persistent problem across the globe. Non-availability of trained staff and infrastructure are the major recognized hurdles in the quality care of these neonates. Hourly progress growth charts and reports are still maintained manually by nurses along with continuous calculation of drug dosage and nutrition as per the changing weight of the baby. iNICU (integrated Neonatology Intensive Care Unit) leverages Beaglebone and Intel Edison based IoT integration with biomedical devices in NICU i.e. monitor, ventilator and blood gas machine. iNICU is hosted on IBM Softlayer based cloud computing infrastructure and map NICU workflow in Java based responsive web application to provide translational research informatics support to the clinicians. iNICU captures real time vital parameters i.e. respiration rate, heart rate, lab data and PACS amounting for millions of data points per day per child. Stream of data is sent to Apache Kafka layer which stores the same in Apache Cassandra NoSQL. iNICU also captures clinical data like feed intake, urine output, and daily assessment of child in PostgreSQL database. It acts as first Big Data hub (of both structured and unstructured data) of neonates across India offering temporal (longitudinal) data of their stay in NICU and allow clinicians in evaluating efficacy of their interventions. iNICU leverages drools based clinical rule based engine and deep learning based big data analytical model coded in R and PMML. iNICU solution aims to improve care time, fills skill gap, enable remote monitoring of neonates in rural regions, assists in identifying the early onset of disease, and reduction in neonatal mortality.
[Mh] Termos MeSH primário: Unidades de Terapia Intensiva Neonatal
[Mh] Termos MeSH secundário: Seres Humanos
Índia
Recém-Nascido
Recém-Nascido Prematuro
População Rural
Fluxo de Trabalho
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1801
[Cu] Atualização por classe:180118
[Lr] Data última revisão:
180118
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170728
[St] Status:MEDLINE
[do] DOI:10.1007/s10916-017-0774-8


  7 / 2506 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
[PMID]:27770368
[Au] Autor:Ilnytskyy S; Bilichak A
[Ad] Endereço:Department of Biological Sciences, University of Lethbridge, 4401 University Drive, Lethbridge, AB, Canada, T1K 3M4. slava.ilyntskyy@uleth.ca.
[Ti] Título:Bioinformatics Analysis of Small RNA Transcriptomes: The Detailed Workflow.
[So] Source:Methods Mol Biol;1456:197-224, 2017.
[Is] ISSN:1940-6029
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Next-generation sequencing became a method of choice for the investigation of small RNA transcriptomes in plants and animals. Although a technical side of sequencing itself is becoming routine, and experimental costs are affordable, data analysis still remains a challenge, especially for researchers with limited computational experience. Here, we present a detailed description of a computational workflow designed to take raw sequencing reads as input, to obtain small RNA predictions, and to detect the differentially expressed microRNAs as a result. The exact commands and pieces of code are provided and hopefully can be adapted and used by other researchers to facilitate the study of small RNA regulation.
[Mh] Termos MeSH primário: Biologia Computacional/métodos
Perfilação da Expressão Gênica
Pequeno RNA não Traduzido/genética
Transcriptoma
[Mh] Termos MeSH secundário: Brassica/genética
Biblioteca Gênica
Genômica/métodos
MicroRNAs/genética
Controle de Qualidade
RNA Interferente Pequeno/genética
Análise de Sequência de RNA
Software
Navegador
Fluxo de Trabalho
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Nm] Nome de substância:
0 (MicroRNAs); 0 (RNA, Small Interfering); 0 (RNA, Small Untranslated)
[Em] Mês de entrada:1801
[Cu] Atualização por classe:180112
[Lr] Data última revisão:
180112
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:161023
[St] Status:MEDLINE


  8 / 2506 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
Texto completo
[PMID]:29261781
[Au] Autor:Perez-Riverol Y; Kuhn M; Vizcaíno JA; Hitz MP; Audain E
[Ad] Endereço:European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.
[Ti] Título:Accurate and fast feature selection workflow for high-dimensional omics data.
[So] Source:PLoS One;12(12):e0189875, 2017.
[Is] ISSN:1932-6203
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:We are moving into the age of 'Big Data' in biomedical research and bioinformatics. This trend could be encapsulated in this simple formula: D = S * F, where the volume of data generated (D) increases in both dimensions: the number of samples (S) and the number of sample features (F). Frequently, a typical omics classification includes redundant and irrelevant features (e.g. genes or proteins) that can result in long computation times; decrease of the model performance and the selection of suboptimal features (genes and proteins) after the classification/regression step. Multiple algorithms and reviews has been published to describe all the existing methods for feature selection, their strengths and weakness. However, the selection of the correct FS algorithm and strategy constitutes an enormous challenge. Despite the number and diversity of algorithms available, the proper choice of an approach for facing a specific problem often falls in a 'grey zone'. In this study, we select a subset of FS methods to develop an efficient workflow and an R package for bioinformatics machine learning problems. We cover relevant issues concerning FS, ranging from domain's problems to algorithm solutions and computational tools. Finally, we use seven different proteomics and gene expression datasets to evaluate the workflow and guide the FS process.
[Mh] Termos MeSH primário: Algoritmos
Bases de Dados como Assunto
Genômica/métodos
Fluxo de Trabalho
[Mh] Termos MeSH secundário: Seres Humanos
Análise Multivariada
Análise de Componente Principal
Máquina de Vetores de Suporte
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1801
[Cu] Atualização por classe:180108
[Lr] Data última revisão:
180108
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:171221
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pone.0189875


  9 / 2506 MEDLINE  
              first record previous record next record last record
seleciona
para imprimir
Fotocópia
[PMID]:29199800
[Au] Autor:Lukkarinen T; Janhunen H; Harjola VP
[Ti] Título:Straightforward emergency care.
[So] Source:Duodecim;132(24):2399-403, 2016.
[Is] ISSN:0012-7183
[Cp] País de publicação:Finland
[La] Idioma:eng
[Ab] Resumo:Emergency department is a showroom of its organization and an entry point to the hospital. The negative impact of sluggish processes and overcrowding in the ED is well acknowledged. Several tools can be used to improve patient flow in the ED. The specialty of emergency medicine is a crucial element which enables the establishment of stable, well-educated staff in the ED.
[Mh] Termos MeSH primário: Serviço Hospitalar de Emergência/organização & administração
[Mh] Termos MeSH secundário: Aglomeração
Eficiência Organizacional
Serviço Hospitalar de Emergência/recursos humanos
Seres Humanos
Melhoria de Qualidade
Fatores de Tempo
Fluxo de Trabalho
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1801
[Cu] Atualização por classe:180108
[Lr] Data última revisão:
180108
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:171205
[St] Status:MEDLINE


  10 / 2506 MEDLINE  
              first record previous record
seleciona
para imprimir
Fotocópia
Texto completo
[PMID]:29194338
[Au] Autor:Bristol AA; Nibbelink CW; Gephart SM; Carrington JM
[Ad] Endereço:School of Nursing, Loma Linda University, Loma Linda, California (Dr Bristol); and College of Nursing, The University of Arizona, Tucson (Drs Nibbelink, Gephart, and Carrington).
[Ti] Título:Nurses' Use of Positive Deviance When Encountering Electronic Health Records-Related Unintended Consequences.
[So] Source:Nurs Adm Q;42(1):E1-E11, 2018 Jan/Mar.
[Is] ISSN:1550-5103
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:As organizations adopt electronic health records (EHRs), nurses frequently encounter system barriers and difficulty performing role expectations. This article describes nurses' experiences with unintended consequences emerging from the use of an EHR. In some situations, nurses were positively deviant when encountering unintended consequences relating to EHRs to accomplish patient care or protect patient safety. Nurses engaged in work-arounds to provide patient care when the EHR did not meet their needs, sometimes in positively deviant ways. Qualitative data were collected from 5 open-ended questions at the end of a quantitative survey. Analysis included coding of responses and organization of processes in line with the triangle model, a human factors framework, to identify overarching themes. Five themes emerged: (1) User support after implementation of EHR; (2) User satisfaction with EHR; (3) Communication for patient care, quality, and safety; (4) Effort to complete tasks; and (5) Areas for improvement. Nurses' ability to adopt positive deviance as they experience unintended consequences offers opportunities for organizations to engage nursing perspectives in improving the EHR and engineer it to be more resilient to nursing work.
[Mh] Termos MeSH primário: Atitude Frente aos Computadores
Registros Eletrônicos de Saúde
Processo de Enfermagem
Resolução de Problemas
[Mh] Termos MeSH secundário: Adulto
Idoso
Sistemas de Apoio a Decisões Clínicas
Feminino
Seres Humanos
Masculino
Meia-Idade
Informática em Enfermagem
Pesquisa Qualitativa
Inquéritos e Questionários
Fluxo de Trabalho
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1712
[Cu] Atualização por classe:171218
[Lr] Data última revisão:
171218
[Sb] Subgrupo de revista:N
[Da] Data de entrada para processamento:171202
[St] Status:MEDLINE
[do] DOI:10.1097/NAQ.0000000000000264



página 1 de 251 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