Publications
171 results found
Ethier J-F, Dameron O, Curcin V, et al., 2013, A unified structural/terminological interoperability framework based on LexEVS: application to TRANSFoRm, Journal of the American Medical Informatics Association, Vol: 20, Pages: 986-994, ISSN: 1527-974X
Objective Biomedical research increasingly relies onthe integration of information from multipleheterogeneous data sources. Despite the fact thatstructural and terminological aspects of interoperabilityare interdependent and rely on a common set ofrequirements, current efforts typically address them inisolation. We propose a unified ontology-basedknowledge framework to facilitate interoperabilitybetween heterogeneous sources, and investigate if usingthe LexEVS terminology server is a viable implementationmethod.Materials and methods We developed a frameworkbased on an ontology, the general information model(GIM), to unify structural models and terminologies,together with relevant mapping sets. This allowed auniform access to these resources within LexEVS tofacilitate interoperability by various components and datasources from implementing architectures.Results Our unified framework has been tested in thecontext of the EU Framework Program 7 TRANSFoRmproject, where it was used to achieve data integration ina retrospective diabetes cohort study. The GIM wassuccessfully instantiated in TRANSFoRm as the clinicaldata integration model, and necessary mappings werecreated to support effective information retrieval forsoftware tools in the project.Conclusions We present a novel, unifying approach toaddress interoperability challenges in heterogeneous datasources, by representing structural and semantic modelsin one framework. Systems using this architecture canrely solely on the GIM that abstracts over both thestructure and coding. Information models, terminologiesand mappings are all stored in LexEVS and can beaccessed in a uniform manner (implementing the HL7CTS2 service functional model). The system is flexibleand should reduce the effort needed from data sourcespersonnel for implementing and managing theintegration.
Curcin V, Danger R, Kuchinke W, et al., 2013, Provenance model for randomized controlled trials, Studies in Computational Intelligence, Vol: 426, Pages: 3-33, ISSN: 1860-949X
This chapter proposes a provenance model for the clinical research domain, focusing on the planning and conduct of randomized controlled trials, and the subsequent analysis and reporting of results from those trials. We look at the provenance requirements for clinical research and trial management of different stakeholders (researchers, clinicians, participants, IT staff) to identify elements needed at multiple levels and stages of the process. In order to address these challenges, a provenance model is defined by extending the Open Provenance Model with domain-specific additions that tie the representation closer to the expertise of medical users, and with the ultimate aim of creating the first OPM profile for randomized controlled clinical trials. As a starting point, we used the domain information model developed at University of Dusseldorf, which conforms to the ICH Guideline for Good Clinical Practice (GCP) standard, thereby ensuring the wider applicability of our work. The application of the model is demonstrated on several examples and queries based on the integrated trial data being captured as part of the TRANSFoRm EU FP7 project. © Springer-Verlag Berlin Heidelberg 2013.
Khunti K, Weston C, Gholap N, et al., 2013, All-cause mortality in relation to glycated haemoglobin in individuals with newly diagnosed type 2 diabetes: A retrospective cohort study, British Journal of Diabetes and Vascular Disease, Vol: 13, Pages: 22-30, ISSN: 1474-6514
Aims: To explore the effect of glycated haemoglobin A1C (HbA1C) on all cause mortality in individuals newly diagnosed with type 2 diabetes, with and without previous cardiovascular disease. Methods: We identified a total of 110,372 of individuals aged 18 to 80 years newly diagnosed with type 2 diabetes (including 9721 (8.8%) with established cardiovascular disease before diagnosis of diabetes) from the UK General Practice Research Database from 1990 to 2005. Primary outcome was all cause mortality. Cox proportional hazards models were used to assess the impact of HbA1C on survival. Results: Over a median follow up of 5.2 years (interquartile range 2.9 to 8.1 years) there were 20,481 deaths. The hazard ratios for all cause mortality in individuals without cardiovascular disease, using the category of 6-6.49% as reference, were 1.28 (1.08 to 1.52), 1.16 (1.00 to 1.39), 1.43 (1.20 to 1.72), 1.62 (1.35 to 1.95), 1.80 (1.52 to 2.23), and 2.43 (2.01 to 2.97) for HbA1C categories of < 6.0%, 6.50-6.99%, 7.0-7.49%, 7.5-7.99%, 8.0-8.99%, and > 9.0% respectively. In individuals with established cardiovascular disease a significant increased risk of mortality was observed for HbA1C categories above 8.00%; hazard ratios 1.91 (1.30-2.83) for HbA1C 8.00-8.99% and 1.95 (1.30-2.90) for HbA1C > 9.0%. Conclusions: A target of HbA1C between 6.0 and 6.5% is appropriate for individuals newly diagnosed with type 2 diabetes without cardiovascular disease. However, a target of < 8.0% may be less beneficial in individuals with established cardiovascular disease. © The Author(s) 2012.
Popiel A, Kajdanowicz T, Kazienko P, et al., 2013, Classification Method for Differential Diagnosis Based on the Course of Episode of Care, 8th International Conference on Hybrid Artificial Intelligent Systems (HAIS), Publisher: SPRINGER-VERLAG BERLIN, Pages: 112-121, ISSN: 0302-9743
Curcin V, Keung SNLC, Danger R, et al., 2013, Model-based Auditability of Clinical Trial Recruitment, MEDINFO 2013: PROCEEDINGS OF THE 14TH WORLD CONGRESS ON MEDICAL AND HEALTH INFORMATICS, PTS 1 AND 2, Vol: 192, Pages: 1223-1223, ISSN: 0926-9630
Curcin V, Woodcock T, Reed JE, et al., 2012, CLAHRC Healthcare Improvement Support System (HISS), Pages: 867-870
This demo presents the main features of the CLAHRC Healthcare Improvement Support System (HISS), a data collection and reporting toolkit which has been designed as a collaboration between the Department of Computing at Imperial College London and NIHR CLAHRC [3] initiative to facilitate measurement for improvement in local multidisciplinary healthcare improvement teams. The HISS software toolkit is supporting a larger methodology to implement research into practice through a series of quality improvement projects and managing the design, introduction, spread and sustainability of those improvements. It allows the project teams to design the desired process model, define quantitative improvement measures, and automatically generate a web application for the team members to enter measurement data at regular (typically weekly) intervals, and monitor their progress in real-time.The demo will showcase some common functions of the system on the example of a real-life improvement project. Copyright © 2012 ACM.
Chatu S, Saxena S, Subramanian V, et al., 2012, Time trends in rates of first surgical resection and thiopurine use in crohn's disease: retrospective cohort study, Vol: Suppl 2 A60
S Chatu, S Saxena, V Subramanian, V Curcin, G Yadegarfar, A Majeed, R C Pollok
Danger R, Joy RC, Darlington J, et al., 2012, Access Control for OPM Provenance Graphs, PROVENANCE AND ANNOTATION OF DATA AND PROCESSES, IPAW 2012, Vol: 7525, Pages: 233-235, ISSN: 0302-9743
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- Citations: 1
Curcin V, Soljak M, Majeed A, 2012, Managing and exploiting routinely collected NHS data for research., Inform Prim Care, Vol: 20, Pages: 225-231, ISSN: 1476-0320
INTRODUCTION: Health research using routinely collected National Health Service (NHS) data derived from electronic health records (EHRs) and health service information systems has been growing in both importance and quantity. Wide population coverage and detailed patient-level information allow this data to be applied to a variety of research questions. However, the sensitivity, complexity and scale of such data also hamper researchers from fully exploiting this potential. OBJECTIVE: Here, we establish the current challenges preventing researchers from making optimal use of the data sets at their disposal, on both the legislative and practical levels, and give recommendations as to how these challenges can be overcome. METHOD: A number of projects has recently been launched in the UK to address poor research data-management practices. Rapid Organisation of Healthcare Research Data (ROHRD) at Imperial College, London produced a useful prototype that provides local researchers with a one-stop index of available data sets together with relevant metadata. FINDINGS: Increased transparency of data sets' availability and their provenance leads to better utilisation and facilitates compliance with regulatory requirements. DISCUSSION: Research data resulting from NHS data is often not utilised fully, or is handled in a haphazard manner that prevents full auditability of the research. Furthermore, lack of informatics and data management skills in research teams act as a barrier to implementing more advanced practices, such as provenance capture and detailed, regularly updated, data management strategies. Only by a concerted effort at the levels of research organisations, funding bodies and publishers, can we achieve full transparency and reproducibility of the research.
Vamos E, Harris M, Millett C, et al., 2012, Association of Systolic and diastolic blood pressure levels and all-cause mortality in people with newly diagnosed Type 2 diabetes: a retrospective cohort study, British Medical Journal, Vol: BMJ 2012; 345
Curcin V, Missier P, De Roure D, 2011, Simulating Taverna workflows using stochastic process algebras, CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, Vol: 23, Pages: 1920-1935, ISSN: 1532-0626
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- Citations: 1
Vamos EP, Pape U, Bottle A, et al., 2011, Association of practice size and pay-for-performance with quality of diabetes management in primary care., CMAJ
Alshamsan R, Majeed A, Vamos EP, et al., 2011, Ethnic Differences in Diabetes Management in Patients With and Without Comorbid Medical Conditions: A cross-sectional study, Diabetes Care
de Lusignan S, Liaw S-T, Krause P, et al., 2011, Key concepts to assess the readiness of data for international research: data quality, lineage and provenance, extraction and processing errors, traceability, and curation. Contribution of the IMIA Primary Health Care Informatics Working Group., Yearb Med Inform, Vol: 6, Pages: 112-120
OBJECTIVE: To define the key concepts which inform whether a system for collecting, aggregating and processing routine clinical data for research is fit for purpose. METHODS: Literature review and shared experiential learning from research using routinely collected data. We excluded socio-cultural issues, and privacy and security issues as our focus was to explore linking clinical data. RESULTS: Six key concepts describe data: (1) DATA QUALITY: the core Overarching concept - Are these data fit for purpose? (2) Data provenance: defined as how data came to be; incorporating the concepts of lineage and pedigree. Mapping this process requires metadata. New variables derived during data analysis have their own provenance. (3) Data extraction errors and (4) Data processing errors, which are the responsibility of the investigator extracting the data but need quantifying. (5) Traceability: the capability to identify the origins of any data cell within the final analysis table essential for good governance, and almost impossible without a formal system of metadata; and (6) Curation: storing data and look-up tables in a way that allows future researchers to carry out further research or review earlier findings. CONCLUSION: There are common distinct steps in processing data; the quality of any metadata may be predictive of the quality of the process. Outputs based on routine data should include a review of the process from data origin to curation and publish information about their data provenance and processing method.
Curcin V, Bottle A, Molokhia M, et al., 2010, Towards a scientific workflow methodology for primary care database studies, STATISTICAL METHODS IN MEDICAL RESEARCH, Vol: 19, Pages: 378-393, ISSN: 0962-2802
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- Citations: 5
Murray J, Saxena S, Millett C, et al., 2010, Reductions in risk factors for secondary prevention of coronary heart disease by ethnic group in south-west London: 10-year longitudinal study (1998-2007), FAMILY PRACTICE, Vol: 27, Pages: 430-438, ISSN: 0263-2136
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- Citations: 15
Molokhia M, Curcin V, Majeed A, 2010, <i>Improving pharmacovigilance</i> Use of routinely collected data, BRITISH MEDICAL JOURNAL, Vol: 340, ISSN: 0959-535X
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- Citations: 2
Curcin V, Ghanem M, Guo Y, 2010, Polymorphic type framework for scientific workflows with relational data model, International Journal of Business Process Integration and Management, Vol: 5, Pages: 45+-45+, ISSN: 1741-8763
Curcin V, Ghanem M, Guo Y, 2010, The design and implementation of a workflow analysis tool, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol: 368, Pages: 4193-4208
Hamilton F, Bottle A, Vamos EP, et al., 2010, Impact of a pay for performance incentive scheme on age, sex and socio-economic inequalities in diabetes management in UK primary care, J Amb Care Med
Tzoulaki I, Molokhia M, Curcin V, et al., 2009, Risk of cardiovascular disease and all cause mortality among patients with type 2 diabetes prescribed oral antidiabetes drugs: retrospective cohort study using UK general practice research database, BMJ-BRITISH MEDICAL JOURNAL, Vol: 339, ISSN: 1756-1833
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- Citations: 288
Guo L, Ghanem M, Curcin V, et al., 2009, Intelligent agents in the service-oriented world - An industrial experience report, Proceedings of the ACM International Conferences on Web Intelligence (WI'09).
Millett C, Bottle A, Ng A, et al., 2009, Pay for performance and the quality of diabetes management in individuals with and without co-morbid medical conditions, JOURNAL OF THE ROYAL SOCIETY OF MEDICINE, Vol: 102, Pages: 369-377, ISSN: 0141-0768
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- Citations: 37
Curcin V, Ghanem M, Guo Y, 2009, Analysing scientific workflows with Computational Tree Logic. Journal of Cluster Computing, Journal of Cluster Computing: Special Issue of Recent Advances in e-Science, ISSN: 1386-7857
Motivated by the widespread use of workflow systems in e-Science applications, this article introduces a formal analysis framework for the verification and profiling of the control flow aspects of scientific workflows. The framework relies on process algebras that characterise each workflow component with a process behaviour, which is then used to build a CTL state model that can be reasoned about. We demonstrate the benefits of the approach by modelling the control flow behaviour of the Discovery Net system, one of the earliest workflow-based e-Science systems, and present how some key properties of workflows and individual service utilisation can be queried at design time. Our approach is generic and can be applied easily to modelling workflows developed in any other system. It also provides a formal basis for the comparison of control aspects of e-Science workflow systems and a design method for future systems.
Curcin V, Ghanem M, Guo Y, et al., 2008, Mining adverse drug reactions with e-science workflows., Proceedings of the 4th Cairo International Biomedical Engineering Conference, 2008. CIBEC 2008
Ghanem M, Curcin V, Wendel P, et al., 2008, Building and using analytical workflows in Discovery Net, Data Mining Techniques in Grid Environments. Dubitzky, Werner (Ed)., Publisher: Wiley-Blackwell, Pages: 119-140, ISBN: 9780470512586
The Discovery Net platform is built around a workflow model for integrating distributed data sources and analytical tools. The platform was originally designed to support the design and execution of distributed data mining tasks within a grid-based environment. However, over the years it has evolved into a generic data analysis platform with applications in such diverse areas as bioinformatics, cheminformatics, text mining and business intelligence. In this work we present our experience in designing the platform and map out the evolution paths for a workflow language, and its architecture, that need to address the requirements of different scientific domains.
Toni F, Guo L, 2008, The ArguGRID platform: An overview., Proceedings of the 5th international workshop on Grid Economics and Business Models. . GECON 2008
Molokhia M, McKeigue P, Curcin V, et al., 2008, Statin induced myopathy and myalgia: time trend analysis and comparison of risk associated with statin class from 1991-2006, PLoS One, Vol: 3, Pages: 1-9, ISSN: 1932-6203
BackgroundStatins are widely used as a cholesterol lowering medication, reduce cardiovascular mortality and morbidity in high risk patients; and only rarely cause serious adverse drug reactions (ADRs). UK primary care databases of morbidity and prescription data, which now cover several million people, have potential for more powerful analytical approaches to study ADRs including adjusting for confounders and examining temporal effects.MethodsCase-crossover design in detecting statin associated myopathy ADR in 93, 831 patients, using two independent primary care databases (1991–2006). We analysed risk by drug class, by disease code and cumulative year, exploring different cut-off exposure times and confounding by temporality.ResultsUsing a 12 and 26 week exposure period, large risk ratios (RR) are associated with all classes of statins and fibrates for myopathy: RR 10.6 (9.8–11.4) and 19.9 (17.6–22.6) respectively. At 26 weeks, the largest risks are with fluvastatin RR 33.3 (95% CI 16.8–66.0) and ciprofibrate (with previous statin use) RR 40.5 (95% CI 13.4–122.0). AT 12 weeks the differences between cerivastatin and atorvastatin RR for myopathy were found to be significant, RR 2.05 (95% CI 1.2–3.5), and for rosuvastatin and fluvastatin RR 3.0 (95% CI 1.6–5.7). After 12 months of statin initiation, the relative risk for myopathy for all statins and fibrates increased to 25.7 (95% CI 21.8–30.3). Furthermore, this signal was detected within 2 years of first events being recorded. Our data suggests an annual incidence of statin induced myopathy or myalgia of around 11.4 for 16, 591 patients or 689 per million per year.ConclusionThere may be differential risks associated with some classes of statin and fibrate. Myopathy related to statin or fibrate use may persist after a long exposure time (12 months or more). These methods could be applied for early detection of harmful drug side effects, using similar primary care diagno
Curcin V, Ghanem M, 2008, Scientific workflow systems - can one size fit all?, Cairo International Biomedical Engineering Conference, Publisher: IEEE, Pages: 285-293, ISSN: 2156-6097
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- Citations: 2
Curcin V, Ghanem M, Molokhia M, et al., 2008, MINING ADVERSE DRUG REACTIONS WITH E-SCIENCE WORKFLOWS, Cairo International Biomedical Engineering Conference, Publisher: IEEE, Pages: 326-+, ISSN: 2156-6097
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