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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Outlier effects on robust joint modelling of longitudinal and survival date

McCrink, L. M. January 2014 (has links)
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.
2

Analysis, visualisation and simulation of sensor data within intelligent environments

Synnott, Jonathan January 2013 (has links)
Reductions in fertility combined with increases in life expectancy are resulting in a globally ageing population. The result is an increasing strain on healthcare resources as members of the older population are more prone to suffer from chronic illness hence requiring long-term care and management. One current focus of research is to investigate methods of alleviating the increased strain on healthcare resources through the use of intelligent environments (IEs). IEs incorporate the use of sensor technology to facilitate long-term, home-based assessment of health condition with the goal of minimising the amount of direct clinical supervision required whilst maximising the frequency and objectivity of patient data collection. This thesis presents the design, development, testing and evaluation of novel methods for the assessment, visualisation and simulation of sensor data generated within IEs. Details of two novel methods for the objective assessment of the severity of the motor symptoms associated with Parkinson's disease are presented. The first method utilises the Nintendo Wii Remote for interaction with motor tasks and the second method uses a computer vision-based approach to monitor activity of daily living performance. Both methods were capable of quantifying the presence of tremor during activity performance. A novel method for IE data visualisation is also presented in the thesis. This method was capable of visualising spatiotemporal data trends using a novel density ring format within 2-dimensional (2D) virtual environments (VEs). Testing on data collected from an active smart lab illustrated the ability of the approach to highlight typical and atypical activity trends. Additionally, a novel method for the simulation of IE data is presented. This method was capable of facilitating the generation of simulated IE datasets through the navigation of an avatar through user-created 2D VEs, facilitating rapid prototyping without access to a physical IE implementation.
3

Exploring systems usage at the feature level by reconceptualizing the dependent variable as a formative construct

Shaw, Norman January 2011 (has links)
IT systems represent large investments in time and money and yet there is a productivity paradox‘ where productivity gains are less than expected. With today‘s powerful computers, the ability of users to adopt new features is being challenged by the multitude of capabilities that are designed into IT systems. When usage is volitional, some users only deploy basic features while others realize greater benefits through more advanced use. By enhancing feature usage, the return on IT investment can be increased for those systems already implemented. Theories of IT acceptance explain the factors that influence individuals‘ initial use of a system. Theories of IT continuance explain the factors that influence individuals‘ continued use of a system. However, the majority of these studies have been at the system level and have not investigated the feature level. This gap in the literature is addressed by developing theoretical propositions that combine constructs from these theories, in order to explain the factors that influence feature usage in post-adoption. The propositions are represented by a conceptual research model that is explored within the context of professionals who are a special case of volitional users because they apply their expertise with a high degree of autonomy. Past studies have not singled out such users and this gap is addressed by adding constructs to the model in order to answer the question of what factors influence systems usage by professionals. The context of the empirical study is the use of Electronic Medical Records (EMRs). Conforming to a pre-structured design, an interview protocol is developed and used as the template to ask questions of physicians via phone interviews. The results, which are validated through a rigorous well-documented process, supported the theories of technology acceptance and IT continuance by showing that the allocation of time is a dominant factor. In addition, the professional association is able to influence its members, and, in the context of healthcare, the careful design of interventions can help less advanced users become more advanced thereby reducing costs and improving care for the benefit of patients, physicians and other healthcare providers. There are a number of contributions of this research. First, existing theories of acceptance and continuance are validated in the context of healthcare. Secondly, the theories are extended to explain the factors that influence feature usage by professionals. Thirdly, the dependent variable, level of use, is conceptualized as a formative construct and a process of consensus building with a panel of experts is employed as a novel method for validating its content. Finally, the research demonstrates that feature rich systems should be analyzed at the feature level.
4

Analysis of patient-safety related data using statistical modeling

Deng, Lisha January 2013 (has links)
To improve the quality of healthcare service, in particular reducing unintended harm to patients during the delivery of the service, patient safety study has become an important topic since the 1990s. This thesis aims to make a contribution to the patient safety research through statistical modelling based on the analysis of incident reports. Analysis of incident report-based data can use time series methods of count data or point process methods. However, strictly speaking, point process models using exact data should be used, because estimates using point process methods will lead t.o more efficient estimates than using interval-censored count data which discarded information, in particular when the underlying intensity driven the process is very wiggly. We have provided a theoretical analysis using Poisson process as an example to illustrate the efficiency loss in Chapter 5. The thesis also illustrated four case studies related to patient safety data. Safety incident report study and Ventilator-Associated-Pneumonia (VAP) study used time series methods, in particular Poisson log-linear model, to study what factors influence the trends of incidence and whet.her t.he rates of incidence differs amongst different hospital sites. Methicillin-Resistant Staphylococcus aurens (IVIRSA) and Campylobacteriosis study used point process methods, in particular Poisson process models, to study the trends of the incident rates, and what. population groups have higher risk rate and whether the rates of incidence differ amongst hospitals. However, we assumed that the counts/ infections occurred independently, which might be unrealistic for time series/ infectious disease data sometimes, if dependence such as cross infections cannot be neglected. Therefore , we proposed a new method in estimating parameters of the Log-Gaussian Cox process which is often used for clustered events. The method uses importance sampling in conjunction with non-parametric intensity estimation. This method is computationally easier than the Markov Chain Monte Carlo (MCMC) approach. It also appears to be more efficient than the minimum contrast estimating method using the K-function and the pair correlation g-function in the simulation study when the intensity function is smooth.
5

Device-free localisation for assisted living applications

Vance, Philip January 2011 (has links)
Determining the location of individuals 'within indoor locations can be useful in var- ious scenarios including security, gaming and ambient assisted living for the elderly. Healthcare services globally are seeking to allow people to stay in their familiar home environments longer due to the multitude of benefits associated with living in non-clinical environments and technologies to determine an individual's movements are key to ensuring home emergencies can be detected and responded to promptly. Popular localisation technologies are device-based which requires the user to actively take part in the aggregation of context information via wearing a traceable device. Such systems are currently inefficient in terms of the quality of data received and the expense of wearable device units as the user often either mislays the device,' accidentally breaks it or forgets to wear it on a daily basis. ' This work presents a device-free localisation system in which the user is not required to actively take part in the localisation process and therefore can continue their daily routine without the need to wear a traceable device. The principle behind this device-free strategy is the absorption phenomenon of the Received Signal Strength (RSS) of transmitted wireless signals as the human body crosses a transmitter- receiver path. By using transmitter-receiver pairs, the absorption capacity of a human can be shown to exhibit signal patterns which can be used in locating and tracking within an environment. To this end, a new methodology which observes the absorption phenomenon that a human body exhibits on RSS signals is presented. Findings show that detection abilities are possible using a single transmitter-receiver pair, though for localisation, additional nodes are needed. The proposed DFL sys- tem design facilitates the use of a minimum number of wireless nodes with the help of a principal component analysis (peA) based intelligent signal processing tech- nique. Upon presenting the optimal setup for DFL, a new method for localisation is outlined known as the Signature Graph (SG) technique. Results demonstrate that human detection and tracking are possible to within O.6m resolution with a minimal hardware infrastructure.
6

Intelligent monitoring of small transients in a complex non-linear system using artificial neutral networks

D'Souza, Llewellyn Joseph January 2006 (has links)
No description available.
7

Multi-channel GPRS-based mobile telemedicine system with bluetooth and J2ME interfaces

Rasid, Mohd F. A. January 2005 (has links)
One of the emerging issues in m-Health is how best to exploit the mobile communications technologies that are now almost globally available. This thesis describes a multi-channel m-Health system with a Bluetooth interface based on the General Packet Radio Service (GPRS). The challenge here is to produce a system to transmit a patient's biomedical signals directly to a hospital using a mobile phone on a commercial GPRS network. As greater patient mobility gradually becomes a trend in remote monitoring, the integration of medical sensors with global connectivity seems to be the next step in providing telemedicine services. The system samples signals from sensors on the patient, then transmits the incoming digital data over a Bluetooth link to a GPRS mobile phone. The system is equipped with patient user interface programs for the patient to perform the data acquisition process from the sensors. There are two programs available, one being the patient interface on a laptop while the other is the patient interface on a mobile phone. The later interface program is developed based on Java 2 Micro Edition (J2ME) MIDlet suite application. The system is integrated with client-server application programs to allow the monitoring and management of medical data. An application server is responsible for handling the telemedicine session and controlling the client connection request from a remote patient. All the medical data transmitted during a telemedicine session are stored in a database together with the patient information and telemedicine session details for further assessment. These data are available to clinicians as and when required, by accessing the database via browser programs. The prototype system allowed real-world mobile tests to be carried out and provide valuable insights into real user experience with m-Health systems.
8

Semantic matching for the medical domain

Shamdasani, Jetendr January 2011 (has links)
In recent years an effort has been made to find ways of representing data in a more organised and linked manner that is better suited for use by com- puter systems. Ontologies have been considered as a potential means of representing information in a structured way. This is achieved through the introduction of a top level semantic layer for data descriptions. Although ontologies have been seen a possible solution to the problem of data hetero- geneity, there now exists a problem of heterogeneity between ontologies. One approach that has been put forward to address some of the chal- lenges of semantic heterogeneity between ontologies is known as ontology alignment. The majority of the ontology alignment approaches today de- tect a single relationship between ontology features, namely equivalence. In this thesis an algorithm is presented which is able to discover subsumption as well as equivalence relationships between concepts in two ontologies. This thesis presents a domain specific solution to the problem of semantic matching by modifying the SMatch algorithm to function in the medical do- main. The SMatch approach uses a single source of background knowledge, the WordNet thesaurus. Using a general resource as a source of background knowledge is not always idealy suited to the problem of semantic matching in the domain of medicine. This work removes the reliance of the SMatch algorithm on WordNet to make it applicable to the specific terminology of the medical domain. This is done by using the UMLS metathesaurus.
9

Ontology based privacy compliance for health data disclosure in Europe

Rahmouni, Hanene Boussi January 2011 (has links)
The harmonization of data protection law in Europe has been theoretically achieved by means of the EU directive on data protection. In practice, the harmonization is not absolute and conflicts continue to exist in the ways Member States are implementing the directive. The integration of different European medical systems will continue to be challenging if technology does not intervene to enhance interoperability between national regulatory frameworks on data protection. In fact, the gap between high level regulations and organisational processes of privacy management in both intellectual and operational terms, dramatically scale within a multi-jurisdictional environment. When sharing medical data between different health organisations in Europe, it is important that the different parties involved in the sharing handle the data in the way indicated by the legislation of the Member State where the data was originally collected, as the requirements might differ from one State to another. Privacy requirements, such as patient consent, may be subject to conflicting conditions between different national frameworks as well as between different legal and ethical frameworks of even a single Member State. This is due first to the fact that, subject to the provision of suitable safeguards, the directive leaves some space for Member States to lay down simplifications and exemptions to some of the obligations that are dictated; such as the obligation to notify the data subject of the processing of their data. Consequently, the legal frameworks in some Member States tend to be less favourable to the processing of personal data for medical research than others. The problem, researchers must then face, is how to comply with multi jurisdiction requirements when working across national borders. In this thesis, we present an approach to enhance privacy compliance when sharing patient data across European domains and ensure its enforcement internally and within external domains where the data might travel. This approach is based on the semantic modelling of privacy obligations that are of legal, ethical or cultural nature. These requirements are for the sharing of personal data between different European Member States. Our model reflects both similarities and conflicts, if any, between the different Member States. The semantic model is thereafter used to tackle three crucial compliance management issues that are: first, increasing privacy awareness within the medical users' community; second, explicitly integrating legal requirements of privacy within access control policies adopted by existing distributed infrastructures such as the grid; third, the modelling of privacy requirements will be also used to allow the auditing of compliance of privacy aware access control policies and the high level privacy guidelines our system initially offer to medical users. In conclusion this research contributes to bridging the gap between high level privacy regulations and organisational processes of privacy management; both human and operational processes.
10

Evaluating complex interventions using routinely collected data : methods to improve the validity of randomised controlled trials and observational studies

Steventon, A. January 2015 (has links)
This thesis addresses the evaluation of complex interventions using routinely collected data, specifically the internal validity of observational studies and the generalisability of Randomised Controlled Trials (RCTs). Following a literature review, this thesis has four main objectives: to estimate the effect of telephone health coaching on hospital utilisation in an observational study; to assess optimal choices of control area in observational studies; to estimate the effect of telehealth within a large RCT; and to develop methods to assess aspects of the generalisability of RCTs empirically. The first paper compares health-coached patients with matched controls. Controls were selected from areas of England that were first matched to the characteristics of the intervention area. Health coaching did not reduce hospital admissions in this study. A second paper uses simulations to assess the relative bias and statistical precision in the treatment effects estimated under alternative approaches to selecting control areas. Lower bias is reported when using local controls than when selecting controls from matched areas, except when there is little unexplained area-level variation in outcomes, when the opposite is true. The third paper reports that, in the RCT, telehealth patients had fewer hospital admissions than controls, but admissions increased unexpectedly among controls after recruitment, leading to concerns about generalisability. Placebo tests find that control patients in the RCT experienced more admissions than matched non-participants receiving usual care. To address the concern that the control group did not receive ‘usual care’, sensitivity analyses are presented that contrast outcomes between the telehealth patients in the RCT and matched non-participants. In this comparison, telehealth is associated with a trend towards more admissions than usual care. The thesis concludes that careful control matching and placebo tests can address important aspects of the validity of observational studies and RCTs, but that further development of evaluation methods is warranted.

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