1 resultado para Predicting treatment time
em Brunel University
Filtro por publicador
- Abertay Research Collections - Abertay University’s repository (2)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (4)
- Aston University Research Archive (2)
- B-Digital - Universidade Fernando Pessoa - Portugal (1)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (11)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (121)
- Biblioteca Virtual del Sistema Sanitario Público de Andalucía (BV-SSPA), Junta de Andalucía. Consejería de Salud y Bienestar Social, Spain (15)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (36)
- Brock University, Canada (4)
- Brunel University (1)
- CentAUR: Central Archive University of Reading - UK (39)
- CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal (1)
- Cochin University of Science & Technology (CUSAT), India (5)
- Collection Of Biostatistics Research Archive (4)
- Consorci de Serveis Universitaris de Catalunya (CSUC), Spain (20)
- CUNY Academic Works (1)
- Digital Archives@Colby (1)
- Digital Commons - Michigan Tech (2)
- Digital Commons @ DU | University of Denver Research (2)
- Digital Commons at Florida International University (2)
- Digital Repository at Iowa State University (1)
- DigitalCommons@The Texas Medical Center (7)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (21)
- DRUM (Digital Repository at the University of Maryland) (1)
- Duke University (1)
- Glasgow Theses Service (1)
- Institute of Public Health in Ireland, Ireland (1)
- Instituto Nacional de Saúde de Portugal (1)
- Instituto Politécnico do Porto, Portugal (8)
- Instituto Superior de Psicologia Aplicada - Lisboa (1)
- Iowa Publications Online (IPO) - State Library, State of Iowa (Iowa), United States (5)
- Lume - Repositório Digital da Universidade Federal do Rio Grande do Sul (1)
- Massachusetts Institute of Technology (1)
- National Center for Biotechnology Information - NCBI (2)
- Nottingham eTheses (1)
- Publishing Network for Geoscientific & Environmental Data (7)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (1)
- Repositório Científico da Universidade de Évora - Portugal (1)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (6)
- Repositório da Produção Científica e Intelectual da Unicamp (9)
- Repositório digital da Fundação Getúlio Vargas - FGV (2)
- Repositório Digital da UNIVERSIDADE DA MADEIRA - Portugal (1)
- Repositório do Centro Hospitalar de Lisboa Central, EPE - Centro Hospitalar de Lisboa Central, EPE, Portugal (3)
- Repositório Institucional da Universidade de Brasília (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (99)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (9)
- Scielo España (1)
- Scielo Saúde Pública - SP (83)
- Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom (1)
- SerWisS - Server für Wissenschaftliche Schriften der Fachhochschule Hannover (1)
- Universidad de Alicante (2)
- Universidad del Rosario, Colombia (8)
- Universidad Politécnica de Madrid (4)
- Universidade do Minho (8)
- Universidade Federal do Pará (3)
- Universidade Federal do Rio Grande do Norte (UFRN) (17)
- Universidade Metodista de São Paulo (4)
- Universidade Técnica de Lisboa (1)
- Universitat de Girona, Spain (5)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (1)
- Université de Lausanne, Switzerland (238)
- Université de Montréal (1)
- Université de Montréal, Canada (11)
- University of Michigan (2)
- University of Queensland eSpace - Australia (33)
- University of Southampton, United Kingdom (1)
Resumo:
Developing a robust method to study characteristics of vascular flow using ultrasound may be useful to assess endothelial function and vasodilatation. There are four stages in this proposal. 1.The first stage is to standardise and validate the methodology to enable computational risk flow data and other flow characteristics to be used clinically. (Current Study). Further development of fluid modelling methods will enable particulate haemodynamics to be investigated, and incorporate detailed endothelial structure together with cellular pathways. 2. This should be followed up by studies in different patient groups investigating the association between the derived values and estimated risk (using other methods such as Framingham risk score). 3. Then, associated with underlying cardiovascular risk, prospective studies would be made to establish whether computational flow dynamic data can predict outcome. If successful it could prove to be a very useful marker of benefit following treatment in a clinical setting.