Outlier effects on robust joint modelling of longitudinal and survival data

Robust joint modelling is an emerging field of research. Through the advancements in electronic patient healthcare records, the popularly of joint modelling approaches has grown rapidly in recent years providing simultaneous analysis of longitudinal and survival data. This research advances previous work through the development of a novel robust joint modelling methodology for one of the most common types of standard joint models, that which links a linear mixed model with a Cox proportional hazards model. Through t-distributional assumptions, longitudinal outliers are accommodated with their detrimental impact being down weighed and thus providing more efficient and reliable estimates. The robust joint modelling technique and its major benefits are showcased through the analysis of Northern Irish end stage renal disease patients. With an ageing population and growing prevalence of chronic kidney disease within the United Kingdom, there is a pressing demand to investigate the detrimental relationship between the changing haemoglobin levels of haemodialysis patients and their survival. As outliers within the NI renal data were found to have significantly worse survival, identification of outlying individuals through robust joint modelling may aid nephrologists to improve patient's survival. A simulation study was also undertaken to explore the difference between robust and standard joint models in the presence of increasing proportions and extremity of longitudinal outliers. More efficient and reliable estimates were obtained by robust joint models with increasing contrast between the robust and standard joint models when a greater proportion of more extreme outliers are present. Through illustration of the gains in efficiency and reliability of parameters when outliers exist, the potential of robust joint modelling is evident. The research presented in this thesis highlights the benefits and stresses the need to utilise a more robust approach to joint modelling in the presence of longitudinal outliers.

Improving Readability of Swedish Electronic Health Records through Lexical Simplification : First Results

This paper describes part of an ongoing effort to improve the readability of Swedish electronic health records (EHRs). An EHR contains systematic documentation of a single patient’s medical history across time, entered by healthcare professionals with the purpose of enabling safe and informed care. Linguistically, medical records exemplify a highly specialised domain, which can be superficially characterised as having telegraphic sentences involving displaced or missing words, abundant abbreviations, spelling variations including misspellings, and terminology. We report results on lexical simplification of Swedish EHRs, by which we mean detecting the unknown, out-ofdictionary words and trying to resolve them either as compounded known words, abbreviations or misspellings.

Infrared image enhancement based on hybrid-domain consideration and data fusion methods

Au cours des dernières décennies, l’effort sur les applications de capteurs infrarouges a largement progressé dans le monde. Mais, une certaine difficulté demeure, en ce qui concerne le fait que les objets ne sont pas assez clairs ou ne peuvent pas toujours être distingués facilement dans l’image obtenue pour la scène observée. L’amélioration de l’image infrarouge a joué un rôle important dans le développement de technologies de la vision infrarouge de l’ordinateur, le traitement de l’image et les essais non destructifs, etc. Cette thèse traite de la question des techniques d’amélioration de l’image infrarouge en deux aspects, y compris le traitement d’une seule image infrarouge dans le domaine hybride espacefréquence, et la fusion d’images infrarouges et visibles employant la technique du nonsubsampled Contourlet transformer (NSCT). La fusion d’images peut être considérée comme étant la poursuite de l’exploration du modèle d’amélioration de l’image unique infrarouge, alors qu’il combine les images infrarouges et visibles en une seule image pour représenter et améliorer toutes les informations utiles et les caractéristiques des images sources, car une seule image ne pouvait contenir tous les renseignements pertinents ou disponibles en raison de restrictions découlant de tout capteur unique de l’imagerie. Nous examinons et faisons une enquête concernant le développement de techniques d’amélioration d’images infrarouges, et ensuite nous nous consacrons à l’amélioration de l’image unique infrarouge, et nous proposons un schéma d’amélioration de domaine hybride avec une méthode d’évaluation floue de seuil amélioré, qui permet d’obtenir une qualité d’image supérieure et améliore la perception visuelle humaine. Les techniques de fusion d’images infrarouges et visibles sont établies à l’aide de la mise en oeuvre d’une mise en registre précise des images sources acquises par différents capteurs. L’algorithme SURF-RANSAC est appliqué pour la mise en registre tout au long des travaux de recherche, ce qui conduit à des images mises en registre de façon très précise et des bénéfices accrus pour le traitement de fusion. Pour les questions de fusion d’images infrarouges et visibles, une série d’approches avancées et efficaces sont proposés. Une méthode standard de fusion à base de NSCT multi-canal est présente comme référence pour les approches de fusion proposées suivantes. Une approche conjointe de fusion, impliquant l’Adaptive-Gaussian NSCT et la transformée en ondelettes (Wavelet Transform, WT) est propose, ce qui conduit à des résultats de fusion qui sont meilleurs que ceux obtenus avec les méthodes non-adaptatives générales. Une approche de fusion basée sur le NSCT employant la détection comprime (CS, compressed sensing) et de la variation totale (TV) à des coefficients d’échantillons clairsemés et effectuant la reconstruction de coefficients fusionnés de façon précise est proposée, qui obtient de bien meilleurs résultats de fusion par le biais d’une pré-amélioration de l’image infrarouge et en diminuant les informations redondantes des coefficients de fusion. Une procédure de fusion basée sur le NSCT utilisant une technique de détection rapide de rétrécissement itératif comprimé (fast iterative-shrinking compressed sensing, FISCS) est proposée pour compresser les coefficients décomposés et reconstruire les coefficients fusionnés dans le processus de fusion, qui conduit à de meilleurs résultats plus rapidement et d’une manière efficace.

Automated generic integration of flight logbook data into aircraft maintenance systems

The automated transfer of flight logbook information from aircrafts into aircraft maintenance systems leads to reduced ground and maintenance time and is thus desirable from an economical point of view. Until recently, flight logbooks have not been managed electronically in aircrafts or at least the data transfer from aircraft to ground maintenance system has been executed manually. Latest aircraft types such as the Airbus A380 or the Boeing 787 do support an electronic logbook and thus make an automated transfer possible. A generic flight logbook transfer system must deal with different data formats on the input side – due to different aircraft makes and models – as well as different, distributed aircraft maintenance systems for different airlines as aircraft operators. This article contributes the concept and top level distributed system architecture of such a generic system for automated flight log data transfer. It has been developed within a joint industry and applied research project. The architecture has already been successfully evaluated in a prototypical implementation.

Legal requirements on secondary use of medical data in the EU and USA – A case study

The use of secondary data in health care research has become a very important issue over the past few years. Data from the treatment context are being used for evaluation of medical data for external quality assurance, as well as to answer medical questions in the form of registers and research databases. Additionally, the establishment of electronic clinical systems like data warehouses provides new opportunities for the secondary use of clinical data. Because health data is among the most sensitive information about an individual, the data must be safeguarded from disclosure.

Understanding near Fermi-level electronic structure through x-ray emission spectroscopy

Thesis (Ph.D.)--University of Washington, 2016-08

Validation of Electronic Health Record Phenotyping of Bipolar Disorder Cases and Controls

Objective: The study was designed to validate use of elec-tronic health records (EHRs) for diagnosing bipolar disorder and classifying control subjects. Method: EHR data were obtained from a health care system of more than 4.6 million patients spanning more than 20 years. Experienced clinicians reviewed charts to identify text features and coded data consistent or inconsistent with a diagnosis of bipolar disorder. Natural language processing was used to train a diagnostic algorithm with 95% specificity for classifying bipolar disorder. Filtered coded data were used to derive three additional classification rules for case subjects and one for control subjects. The positive predictive value (PPV) of EHR-based bipolar disorder and subphenotype di- agnoses was calculated against diagnoses from direct semi- structured interviews of 190 patients by trained clinicians blind to EHR diagnosis. Results: The PPV of bipolar disorder defined by natural language processing was 0.85. Coded classification based on strict filtering achieved a value of 0.79, but classifications based on less stringent criteria performed less well. No EHR- classified control subject received a diagnosis of bipolar dis- order on the basis of direct interview (PPV=1.0). For most subphenotypes, values exceeded 0.80. The EHR-based clas- sifications were used to accrue 4,500 bipolar disorder cases and 5,000 controls for genetic analyses. Conclusions: Semiautomated mining of EHRs can be used to ascertain bipolar disorder patients and control subjects with high specificity and predictive value compared with diagnostic interviews. EHRs provide a powerful resource for high-throughput phenotyping for genetic and clinical research.

A methodology for spreadsheet development based on data structure

Abstract not available

Federated architecture for biomedical data integration

The last decades have been characterized by a continuous adoption of IT solutions in the healthcare sector, which resulted in the proliferation of tremendous amounts of data over heterogeneous systems. Distinct data types are currently generated, manipulated, and stored, in the several institutions where patients are treated. The data sharing and an integrated access to this information will allow extracting relevant knowledge that can lead to better diagnostics and treatments. This thesis proposes new integration models for gathering information and extracting knowledge from multiple and heterogeneous biomedical sources. The scenario complexity led us to split the integration problem according to the data type and to the usage specificity. The first contribution is a cloud-based architecture for exchanging medical imaging services. It offers a simplified registration mechanism for providers and services, promotes remote data access, and facilitates the integration of distributed data sources. Moreover, it is compliant with international standards, ensuring the platform interoperability with current medical imaging devices. The second proposal is a sensor-based architecture for integration of electronic health records. It follows a federated integration model and aims to provide a scalable solution to search and retrieve data from multiple information systems. The last contribution is an open architecture for gathering patient-level data from disperse and heterogeneous databases. All the proposed solutions were deployed and validated in real world use cases.

Linking electronic journals - Lessons from the Open Journal project

The Open Journal project has completed its three year period of funding by the UK Electronic Libraries (eLib) programme (Rusbridge 1998). During that time, the number of journals that are available electronically leapt from a few tens to a few thousand. Some of these journals are now developing the sort of features the project has been advocating, in particular the use of links within journals, between different primary journals, with secondary journals data, and to non-journal sources. Assessing the achievements of the project and considering some of the difficulties it faced, we report on the different approaches to linking that the project developed, and summarise the important user responses that indicate what works and what does not. Looking ahead, there are signs of change, not just to simple linking within journals but to schemes in which links are the basis of "distributed" journals, where information may be shared and documents built from different sources. The significance has yet to be appreciated, but this would be a major change from printed journals. If projects such as this and others have provided the initial impetus, the motivation for distributed journals comes, perhaps surprisingly, from within certain parts of the industry, as the paper shows.

An assessment of data leakage in Firefox under different conditions.

Data leakage is a serious issue and can result in the loss of sensitive data, compromising user accounts and details, potentially affecting millions of internet users. This paper contributes to research in online security and reducing personal footprint by evaluating the levels of privacy provided by the Firefox browser. The aim of identifying conditions that would minimize data leakage and maximize data privacy is addressed by assessing and comparing data leakage in the four possible browsing modes: normal and private modes using a browser installed on the host PC or using a portable browser from a connected USB device respectively. To provide a firm foundation for analysis, a series of carefully designed, pre-planned browsing sessions were repeated in each of the various modes of Firefox. This included low RAM environments to determine any effects low RAM may have on browser data leakage. The results show that considerable data leakage may occur within Firefox. In normal mode, all of the browsing information is stored within the Mozilla profile folder in Firefox-specific SQLite databases and sessionstore.js. While passwords were not stored as plain text, other confidential information such as credit card numbers could be recovered from the Form history under certain conditions. There is no difference when using a portable browser in normal mode, except that the Mozilla profile folder is located on the USB device rather than the host's hard disk. By comparison, private browsing reduces data leakage. Our findings confirm that no information is written to the Firefox-related locations on the hard disk or USB device during private browsing, implying that no deletion would be necessary and no remnants of data would be forensically recoverable from unallocated space. However, two aspects of data leakage occurred equally in all four browsing modes. Firstly, all of the browsing history was stored in the live RAM and was therefore accessible while the browser remained open. Secondly, in low RAM situations, the operating system caches out RAM to pagefile.sys on the host's hard disk. Irrespective of the browsing mode used, this may include Firefox history elements which can then remain forensically recoverable for considerable time.

From Cash to Electronic Payments: Microeconomic, Macroeconomic, and Policy Aspects of Retail Payment Systems

This dissertation explores three aspects of the economics and policy issues surrounding retail payments (low-value frequent payments): the microeconomic aspect, by measuring costs associated with retail payment instruments; the macroeconomic aspect, by quantifying the impact of the use of electronic rather than paper-based payment instruments on consumption and GDP; and the policy aspect, by identifying barriers that keep countries stuck with outdated payment systems, and recommending policy interventions to move forward with payments modernization. Payment system modernization has become a prominent part of the financial sector reform agenda in many advanced and developing countries. Greater use of electronic payments rather than cash and other paper-based instruments would have important economic and social benefits, including lower costs and thereby increased economic efficiency and higher incomes, while broadening access to the financial system, notably for people with moderate and low incomes. The dissertation starts with a general introduction on retail payments. Chapter 1 develops a theoretical model for measuring payments costs, and applies the model to Guyana—an emerging market in the midst of the transition from paper to electronic payments. Using primary survey data from Guyanese consumers, the results of the analysis indicate that annual costs related to the use of cash by consumers reach 2.5 percent of the country’s GDP. Switching to electronic payment instruments would provide savings amounting to 1 percent of GDP per year. Chapter 2 broadens the analysis to calculate the macroeconomic impacts of a move to electronic payments. Using a unique panel dataset of 76 countries across the 17-year span from 1998 to 2014 and a pooled OLS country fixed effects model, Chapter 2 finds that on average, use of debit and credit cards contribute USD 16.2 billion to annual global consumption, and USD 160 billion to overall annual global GDP. Chapter 3 provides an in-depth assessment of the Albanian payment cards and remittances market and recommends a set of incentives and regulations (both carrots and sticks) that would allow the country to modernize its payment system. Finally, the conclusion summarizes the lessons of the dissertation’s research and brings forward issues to be explored by future research in the retail payments area.

An E-government Interoperability Platform Supporting Personal Data Protection Regulations

Public agencies are increasingly required to collaborate with each other in order to provide high-quality e-government services. This collaboration is usually based on the service-oriented approach and supported by interoperability platforms. Such platforms are specialized middleware-based infrastructures enabling the provision, discovery and invocation of interoperable software services. In turn, given that personal data handled by governments are often very sensitive, most governments have developed some sort of legislation focusing on data protection. This paper proposes solutions for monitoring and enforcing data protection laws within an E-government Interoperability Platform. In particular, the proposal addresses requirements posed by the Uruguayan Data Protection Law and the Uruguayan E-government Platform, although it can also be applied in similar scenarios. The solutions are based on well-known integration mechanisms (e.g. Enterprise Service Bus) as well as recognized security standards (e.g. eXtensible Access Control Markup Language) and were completely prototyped leveraging the SwitchYard ESB product.

Hierarchical clustering with multiple-height branch-cut applied to short time-series gene expression data.

Rigid adherence to pre-specified thresholds and static graphical representations can lead to incorrect decisions on merging of clusters. As an alternative to existing automated or semi-automated methods, we developed a visual analytics approach for performing hierarchical clustering analysis of short time-series gene expression data. Dynamic sliders control parameters such as the similarity threshold at which clusters are merged and the level of relative intra-cluster distinctiveness, which can be used to identify "weak-edges" within clusters. An expert user can drill down to further explore the dendrogram and detect nested clusters and outliers. This is done by using the sliders and by pointing and clicking on the representation to cut the branches of the tree in multiple-heights. A prototype of this tool has been developed in collaboration with a small group of biologists for analysing their own datasets. Initial feedback on the tool has been positive.

CATEGORIZATION OF BRAZILIAN INTERNET USERS AND ITS IMPACTS ON THE USE OF ELECTRONIC GOVERNMENT SERVICES

This paper aims to categorize Brazilian Internet users according to the diversity of their online activities and to assess the propensity of these Internet users´ groups to use electronic government (e-gov) services. The Amartya Sen’s Capability Approach was adopted as the theoretical framework for its consideration of people’s freedom to decide on their use of available resources and their competencies for these decisions, leading to the use of e-gov services. Multivariate statistical techniques were used to perform data analysis from the 2007, 2009 and 2011 editions of ICT Household Survey. The results showed that Internet users belonging to the advanced and intermediate use groups were more likely to use e-gov services than those who belong to the sporadic use group. Moreover, the results also demonstrated that the Internet user group of intermediate use presented a higher tendency to use e-gov services than the Internet user group of advanced use. This tendency is possibly related to the extensive use of interactive and collaborative activities of leisure and entertainment performed by this type of user. The findings of this research may be useful in guiding public policies for the dissemination and provision of electronic government services in Brazil.