A review of dynamic Bayesian network techniques with applications in healthcare risk modelling

Coping with an ageing population is a major concern for healthcare organisations around the world. The average cost of hospital care is higher than social care for older and terminally ill patients. Moreover, the average cost of social care increases with the age of the patient. Therefore, it is important to make efficient and fair capacity planning which also incorporates patient centred outcomes. Predictive models can provide predictions which their accuracy can be understood and quantified. Predictive modelling can help patients and carers to get the appropriate support services, and allow clinical decision-makers to improve care quality and reduce the cost of inappropriate hospital and Accident and Emergency admissions. The aim of this study is to provide a review of modelling techniques and frameworks for predictive risk modelling of patients in hospital, based on routinely collected data such as the Hospital Episode Statistics database. A number of sub-problems can be considered such as Length-of-Stay and End-of-Life predictive modelling. The methodologies in the literature are mainly focused on addressing the problems using regression methods and Markov models, and the majority lack generalisability. In some cases, the robustness, accuracy and re-usability of predictive risk models have been shown to be improved using Machine Learning methods. Dynamic Bayesian Network techniques can represent complex correlations models and include small probabilities into the solution. The main focus of this study is to provide a review of major time-varying Dynamic Bayesian Network techniques with applications in healthcare predictive risk modelling.

Using a whole person approach to support people with cancer: a longitudinal, mixed methods service evaluation

Introduction: Improved models of care are needed to meet all the support needs of people with cancer, which encompass psychological, emotional, physical, spiritual, sexual, occupational, social and existential needs. The aim of this paper is to (1) evaluate short and long-term impacts of using a whole person approach to support people with cancer on the Living Well with the Impact of Cancer Course (LWC); (2) use these data to inform strategic decisions about future service provision at Penny Brohn UK. Methods: Longitudinal mixed-methods service evaluation (n=135). Data collected included health related quality of life (HRQoL) (FACIT-SpEx); Concerns (types and severity - MYCaW); lifestyle behaviour (bespoke questionnaire) and participants’ experiences over 12 months post course. Results: Statistically and clinically significant improvements from baseline - 12 months in severity of MYCaW Concerns (n=64; p<0.000) and mean total HRQoL (n=66; p<0.000). The majority of MYCaW concerns were ‘psychological and emotional’ and about participants’ wellbeing. Spiritual, emotional and functional wellbeing contributed most to HRQoL improvements at 12 months. Barriers to maintaining healthy lifestyle changes included lack of support from family and friends, time constraints, and returning to work. 3-6 months post-course was identified as the time when more support was most likely to be needed. Conclusions: Using a whole person approach for the LWC enabled the needs of participants to be met, and statistically and clinically significant improvements in HRQoL and MYCaW Concerns were reported. Qualitative data analysis explored how experiencing whole person support enabled participants to make and sustain healthy lifestyle changes associated with improved survivorship. Barriers experienced to making health behaviour change were also identified. These data then informed wider and more person-centred clinical provision to increase the maintenance of positive long-term behaviour changes. Comparison of whole person approaches to cancer treatment and support and standard care are now urgently needed.

Curriculum and beyond: Mathematics support for first year life science students

The move into higher education is a real challenge for students from all educational backgrounds, with the adaptation to a new curriculum and style of learning and teaching posing a daunting task. A series of exercises were planned to boost the impact of the mathematics support for level four students and was focussed around a core module for all students. The intention was to develop greater confidence in tackling mathematical problems in all levels of ability and to provide more structured transition period in the first semester of level 4. Over a two-year period the teaching team for Biochemistry and Molecular Biology provided a series of structured formative tutorials and “interactive” online problems. Video solutions to all formative problems were made available, in order that students were able to engage with the problems at any time and were not disadvantaged if they could not attend. The formative problems were specifically set to dovetail into a practical report in which the mathematical skills developed were specifically assessed. Students overwhelmingly agreed that the structured formative activities had broadened their understanding of the subject and that more such activities would help. Furthermore, it is interesting to note that the package of changes undertaken resulted in a significant increase in the overall module mark over the two years of development.

Network mechanisms of intentional learning

The ability to learn new tasks rapidly is a prominent characteristic of human behaviour. This ability relies on flex- ible cognitive systems that adapt in order to encode temporary programs for processing non-automated tasks. Previous functional imaging studies have revealed distinct roles for the lateral frontal cortices (LFCs) and the ven- tral striatum in intentional learning processes. However, the human LFCs are complex; they house multiple dis- tinct sub-regions, each of which co-activates with a different functional network. It remains unclear how these LFC networks differ in their functions and how they coordinate with each other, and the ventral striatum, to support intentional learning. Here, we apply a suite of fMRI connectivity methods to determine how LFC networks activate and interact at different stages of two novel tasks, in which arbitrary stimulus-response rules are learnt either from explicit instruction or by trial-and-error. We report that the networks activate en masse and in synchrony when novel rules are being learnt from instruction. However, these networks are not homogeneous in their functions; instead, the directed connectivities between them vary asymmetrically across the learning timecourse and they disengage from the task sequentially along a rostro-caudal axis. Furthermore, when negative feedback indicates the need to switch to alternative stimulus–response rules, there is additional input to the LFC networks from the ventral striatum. These results support the hypotheses that LFC networks interact as a hierarchical system during intentional learning and that signals from the ventral striatum have a driving influence on this system when the internal program for processing the task is updated.

Dynamic Network Mechanisms of Relational Integration

A prominent hypothesis states that specialized neural modules within the human lateral frontopolar cortices (LFPCs) support “relational integration” (RI), the solving of complex problems using inter-related rules. However, it has been proposed that LFPC activity during RI could reflect the recruitment of additional “domain-general” resources when processing more difficult problems in general as opposed to RI specifi- cally. Moreover, theoretical research with computational models has demonstrated that RI may be supported by dynamic processes that occur throughout distributed networks of brain regions as opposed to within a discrete computational module. Here, we present fMRI findings from a novel deductive reasoning paradigm that controls for general difficulty while manipulating RI demands. In accordance with the domain- general perspective, we observe an increase in frontoparietal activation during challenging problems in general as opposed to RI specifically. Nonetheless, when examining frontoparietal activity using analyses of phase synchrony and psychophysiological interactions, we observe increased network connectivity during RI alone. Moreover, dynamic causal modeling with Bayesian model selection identifies the LFPC as the effective connectivity source. Based on these results, we propose that during RI an increase in network connectivity and a decrease in network metastability allows rules that are coded throughout working memory systems to be dynamically bound. This change in connectivity state is top-down propagated via a hierarchical system of domain-general networks with the LFPC at the apex. In this manner, the functional network perspective reconciles key propositions of the globalist, modular, and computational accounts of RI within a single unified framework.

To what extent has research conducted by the GaWC Research Network aided our understanding of large EU law firm geography?

This thesis explores whether a specific group of large EU law firms exhibited multiple common behaviours regarding their EU geographies between 1998 and 2009. These potentially common behaviours included their preferences for trading in certain EU locations, their usage of law firm alliances, and the specific reasons why they opened or closed EU branch offices. If my hypothesis is confirmed, this may indicate that certain aspects of large law firm geography are predictable – a finding potentially of interest to various stakeholders globally, including legal regulators, academics and law firms. In testing my hypothesis, I have drawn on research conducted by the Globalization and World Cities (GaWC) Research Network to assist me. Between 1999 and 2010, the GaWC published seven research papers exploring the geographies of large US and UK law firms. Several of the GaWC’s observations arising from these studies were evidence-based; others were speculative – including a novel approach for explaining legal practice branch office change, not adopted in research conducted previously or subsequently. By distilling the GaWC’s key observations these papers into a series of “sub-hypotheses”, I been able to test whether the geographical behaviours of my novel cohort of large EU law firms reflect those suggested by the GaWC. The more the GaWC’s suggested behaviours are observed among my cohort, the more my hypothesis will be supported. In conducting this exercise, I will additionally evaluate the extent to which the GaWC’s research has aided our understanding of large EU law firm geography. Ultimately, my findings broadly support most of the GaWC’s observations, notwithstanding our cohort differences and the speculative nature of several of the GaWC’s propositions. My investigation has also allowed me to refine several of the GaWC’s observations regarding commonly-observable large law firm geographical behaviours, while also addressing a key omission from the group’s research output.