Handling high level of censoring for endovascular aortic repair risk prediction

Feature selection is important in medical field for many reasons. However, selecting important variables is a difficult task with the presence of censoring that is a unique feature in survival data analysis. This paper proposed an approach to deal with the censoring problem in endovascular aortic repair survival data through Bayesian networks. It was merged and embedded with a hybrid feature selection process that combines cox's univariate analysis with machine learning approaches such as ensemble artificial neural networks to select the most relevant predictive variables. The proposed algorithm was compared with common survival variable selection approaches such as; least absolute shrinkage and selection operator LASSO, and Akaike information criterion AIC methods. The results showed that it was capable of dealing with high censoring in the datasets. Moreover, ensemble classifiers increased the area under the roc curves of the two datasets collected from two centers located in United Kingdom separately. Furthermore, ensembles constructed with center 1 enhanced the concordance index of center 2 prediction compared to the model built with a single network. Although the size of the final reduced model using the neural networks and its ensembles is greater than other methods, the model outperformed the others in both concordance index and sensitivity for center 2 prediction. This indicates the reduced model is more powerful for cross center prediction.

The sensitivity of mapping methods to reference data quality:training supervised image classifications with imperfect reference data

The accuracy of a map is dependent on the reference dataset used in its construction. Classification analyses used in thematic mapping can, for example, be sensitive to a range of sampling and data quality concerns. With particular focus on the latter, the effects of reference data quality on land cover classifications from airborne thematic mapper data are explored. Variations in sampling intensity and effort are highlighted in a dataset that is widely used in mapping and modelling studies; these may need accounting for in analyses. The quality of the labelling in the reference dataset was also a key variable influencing mapping accuracy. Accuracy varied with the amount and nature of mislabelled training cases with the nature of the effects varying between classifiers. The largest impacts on accuracy occurred when mislabelling involved confusion between similar classes. Accuracy was also typically negatively related to the magnitude of mislabelled cases and the support vector machine (SVM), which has been claimed to be relatively insensitive to training data error, was the most sensitive of the set of classifiers investigated, with overall classification accuracy declining by 8% (significant at 95% level of confidence) with the use of a training set containing 20% mislabelled cases.

Watermarking biomedical time series data

This thesis addresses the problem of information hiding in low dimensional digital data focussing on issues of privacy and security in Electronic Patient Health Records (EPHRs). The thesis proposes a new security protocol based on data hiding techniques for EPHRs. This thesis contends that embedding of sensitive patient information inside the EPHR is the most appropriate solution currently available to resolve the issues of security in EPHRs. Watermarking techniques are applied to one-dimensional time series data such as the electroencephalogram (EEG) to show that they add a level of confidence (in terms of privacy and security) in an individual’s diverse bio-profile (the digital fingerprint of an individual’s medical history), ensure belief that the data being analysed does indeed belong to the correct person, and also that it is not being accessed by unauthorised personnel. Embedding information inside single channel biomedical time series data is more difficult than the standard application for images due to the reduced redundancy. A data hiding approach which has an in built capability to protect against illegal data snooping is developed. The capability of this secure method is enhanced by embedding not just a single message but multiple messages into an example one-dimensional EEG signal. Embedding multiple messages of similar characteristics, for example identities of clinicians accessing the medical record helps in creating a log of access while embedding multiple messages of dissimilar characteristics into an EPHR enhances confidence in the use of the EPHR. The novel method of embedding multiple messages of both similar and dissimilar characteristics into a single channel EEG demonstrated in this thesis shows how this embedding of data boosts the implementation and use of the EPHR securely.

The professional role of breast cancer nurses in multi-disciplinary breast cancer care teams

Since the 1970s breast cancer services have witnessed considerable changes in the management of patients. One significant change was the introduction of specialist core personnel, including the breast care nurse (BCN). The role of the BCN has been gaining credence rapidly in the British NHS and this service is perhaps the paradigm of care for other services. With the lack of specific evidence of the role of specialist nurses in the breast care team, the current study aims to explore this area by in-depth interviews with core team members, and observations of 16 multi-disciplinary teams in England. The study explores the following themes: Nurses' unique informal management leadership role in ensuring the co-ordination, communication and planning of the team work; nurses' innovatory role in making the bureaucracy respond to patients and their relatives needs; nurses supportive role in the provision of expert advice and guidance to other members of the team; nurses confidence and humour in well-performing teams; and the limitations of the professional role of the breast cancer nurse. This study indicates that there is evidence that the BCN is practicing at an advanced level of practice. However, there is a severe lack of evidence-based description of that advanced practice. Cancer nurses including the BCNs should develop and participate in programmes of research in line with cancer legislation in order to build an evidence base that ultimately supports their unique role. © 2004 Elsevier Ltd. All rights reserved.

A magnetoencephalographic study of low-level auditory processing in developmental dyslexia

The possibility that developmental dyslexia results from low-level sensory processing deficits has received renewed interest in recent years. Opponents of such sensory-based explanations argue that dyslexia arises primarily from phonological impairments. However, many behavioural correlates of dyslexia cannot be explained sufficiently by cognitive-level accounts and there is anatomical, psychometric and physiological evidence of sensory deficits in the dyslexic population. This thesis aims to determine whether the low-level (pre-attentive) processing of simple auditory stimuli is disrupted in compensated adult dyslexics. Using psychometric and neurophysiological measures, the nature of auditory processing abnormalities is investigated. Group comparisons are supported by analysis of individual data in order to address the issue of heterogeneity in dyslexia. The participant pool consisted of seven compensated dyslexic adults and seven age and IQ matched controls. The dyslexic group were impaired, relative to the control group, on measures of literacy, phonological awareness, working memory and processing speed. Magnetoencephalographic recordings were conducted during processing of simple, non-speech, auditory stimuli. Results confirm that low-level auditory processing deficits are present in compensated dyslexic adults. The amplitude of N1m responses to tone pair stimuli were reduced in the dyslexic group. However, there was no evidence that manipulating either the silent interval or the frequency separation between the tones had a greater detrimental effect on dyslexic participants specifically. Abnormal MMNm responses were recorded in response to frequency deviant stimuli in the dyslexic group. In addition, complete stimulus omissions, which evoked MMNm responses in all control participants, failed to elicit significant MMNm responses in all but one of the dyslexic individuals. The data indicate both a deficit of frequency resolution at a local level of auditory processing and a higher-level deficit relating to the grouping of auditory stimuli, relevant for auditory scene analysis. Implications and directions for future research are outlined.

Adapting an apprenticeship model to the needs of English-medium education at the tertiary level in Turkey

Despite the difficulties that we have regarding the use of English in tertiary education in Turkey, we argue that it is necessary for those involved to study in the medium of English. Furthermore, significant advances have been made on this front. These efforts have been for the most part language-oriented, but also include research into needs analysis and the pedagogy of team-teaching. Considering the current situation at this level of education, however, there still seems to be more to do. And the question is, what more can we do? What further contribution can we make? Or, how can we take this process further? The purpose of the study reported here is to respond to this last question. We test the proposition that it is possible to take this process further by investigating the efficient management of transition from Turkish-medium to English-medium at the tertiary level of education in Turkey. Beyond what is achieved by only the language orientation of the EAP approach, and moving conceptually deeper than what has been achieved by the team-teaching approach, the research undertaken for the purpose of this study focuses on the idea of the discourse community that people want to belong to. It then pursues an adaptation of the essentially psycho-social approach of apprenticeship, as people become aspirants and apprentices to that discourse community. In this thesis, the researcher recognises that she cannot follow all the way through to the full implementation of her ideas in a fully-taught course. She is not in a position to change the education system. What she does here is to introduce a concept and sample its effects in terms of motivation, and thereby of integration and of success, for individuals and groups of learners. Evaluation is provided by acquiring both qualitative and quantitative data concerning mature members' perceptions of apprenticed-neophytes functioning as members in the new community, apprenticed-neophytes' perceptions of their own membership and of the preparation process undertaken, and the comparison of these neophytes' performance with that of other neophytes in the community. The data obtained provide strong evidence in support of the potential usefulness of this apprenticeship model towards the declared purpose of improving the English-medium tertiary education of Turkish students in their chosen fields of study.

A comparison of sales response predictions from demand models applied to store-level versus panel data

In order to generate sales promotion response predictions, marketing analysts estimate demand models using either disaggregated (consumer-level) or aggregated (store-level) scanner data. Comparison of predictions from these demand models is complicated by the fact that models may accommodate different forms of consumer heterogeneity depending on the level of data aggregation. This study shows via simulation that demand models with various heterogeneity specifications do not produce more accurate sales response predictions than a homogeneous demand model applied to store-level data, with one major exception: a random coefficients model designed to capture within-store heterogeneity using store-level data produced significantly more accurate sales response predictions (as well as better fit) compared to other model specifications. An empirical application to the paper towel product category adds additional insights. This article has supplementary material online.

Growth expectations and financial performance of small businesses:evidence from Latvia

By applying regulatory focus theory, this paper investigates the impact of both initial confidence and of exactness of growth expectations on subsequent financial performance of the small firms. Drawing on the unique data set based on the repeated survey design, we make one of the first attempts to explore the complexity of this relationship empirically. Overall the findings suggest that controlling for other relevant factors, including actual growth, the entrepreneurs having higher growth expectations perform significantly better later on in terms of profitability. In addition, education has a strong modifying effect: the impact of high growth expectations on subsequent profit performance is stronger for entrepreneurs with lower level of education.

Calibration of consumer knowledge of the web

Calibration of consumer knowledge of the web refers to the correspondence between accuracy and confidence in knowledge of the web. Being well-calibrated means that a person is realistic in his or her assessment of the level of knowledge that he or she possesses. This study finds that involvement leads to better calibration and that calibration is higher for procedural knowledge and common knowledge, as compared to declarative knowledge and specialized knowledge. Neither usage, nor experience, has any effect on calibration of knowledge of the web. No difference in calibration is observed between genders. But, in agreement with previous findings, this study also finds that males are more confident in their knowledge of the web. The results point out that calibration could be more a function of knowledge-specific factors and less that of individual-specific factors. The study also identifies flow and frustration with the web as consequences of calibration of knowledge of the web and draws the attention of future researchers to examine these aspects.