Detecting and Responding to Concept Drift in Business Processes

Concept drift, which refers to changes in the underlying process structure or customer behaviour over time, is inevitable in business processes, causing challenges in ensuring that the learned model is a proper representation of the new data. Due to factors such as seasonal effects and policy updates, concept drifts can occur in customer transitions and time spent throughout the process, either suddenly or gradually. In a concept drift context, we can discard the old data and retrain the model using new observations (sudden drift) or combine the old data with the new data to update the model (gradual drift) or maintain the model as unchanged (no drift). In this paper, we model a response to concept drift as a sequential decision making problem by combing a hierarchical Markov model and a Markov decision process (MDP). The approach can detect concept drift, retrain the model and update customer profiles automatically. We validate the proposed approach on 68 artificial datasets and a real-world hospital billing dataset, with experimental results showing promising performance

What works, how and in which contexts when supporting parents to implement intensive speech and language therapy at home for children with speech sound disorder? A protocol for a realist review

Introduction Speech and Language Therapists (SLTs) worldwide report challenges with providing recommended, evidence-based intervention intensity for children with speech sound disorder (SSD). Challenges such as service constraints and/or family contexts impact on access to optimal therapy intensity. Existing research indicates that empowering and training parents to deliver intervention at home, alongside SLT support, offers one possible solution to increasing the intensity of intervention children with SSD receive. Digital health could increase accessibility to intensive home-practise and help sustain engagement with therapy activities. Further exploration is needed around what makes parent-implemented interventions for children with speech sound disorder effective, for who, in which situations. This paper outlines the protocol for a realist review which aims to explore the active ingredients and contextual factors of effective digital parent-led interventions.Methods and analysis A realist review will explore the research question, following six stages. The scope of the review will be determined, and initial programme theories will be developed about what works in digital parent-implemented interventions for SSD, for whom, how, why, and in what circumstances. Relevant secondary data, identified through a formal search strategy, will be selected, appraised, analysed, and synthesised using realist principles to test and further refine the initial programme theories. This process will develop refined underpinning explanatory theories which capture the interaction between contexts, mechanisms, and outcomes of the intervention. An expert steering group will provide insight to inform explanatory theories, searches, and dissemination.Ethics and dissemination Ethical approval is not required for this review. The refined programme theories from the review will inform the next stages of a wider study. A subsequent realist evaluation will test and further refine theories with key stakeholders. Following this, the underpinning programme theory will be used to co-produce a digital tool, to support parents to deliver home-intervention alongside SLT support. <br/

Learning Behaviour for Service Personalisation and Adaptation

Context-aware applications within pervasive environments are increasingly being developed as services and deployed in the cloud. As such these services are increasingly required to be adaptive to individual users to meet their specific needs or to reflect the changes of their behavior. To address this emerging challenge this paper introduces a service-oriented personalisation framework for service personalisation with special emphasis being placed on behavior learning for user model and service function adaptation. The paper describes the system architecture and the underlying methods and technologies including modelling and reasoning, behavior analysis and a personalisation mechanism. The approach has been implemented in a service-oriented prototype system, and evaluated in a typical scenario of providing personalised travel assistance for the elderly using the help-on-demand services deployed on smartphone

Options for early breast cancer follow-up in primary and secondary care : a systematic review

Background Both incidence of breast cancer and survival have increased in recent years and there is a need to review follow up strategies. This study aims to assess the evidence for benefits of follow-up in different settings for women who have had treatment for early breast cancer. Method A systematic review to identify key criteria for follow up and then address research questions. Key criteria were: 1) Risk of second breast cancer over time - incidence compared to general population. 2) Incidence and method of detection of local recurrence and second ipsi and contra-lateral breast cancer. 3) Level 1–4 evidence of the benefits of hospital or alternative setting follow-up for survival and well-being. Data sources to identify criteria were MEDLINE, EMBASE, AMED, CINAHL, PSYCHINFO, ZETOC, Health Management Information Consortium, Science Direct. For the systematic review to address research questions searches were performed using MEDLINE (2011). Studies included were population studies using cancer registry data for incidence of new cancers, cohort studies with long term follow up for recurrence and detection of new primaries and RCTs not restricted to special populations for trials of alternative follow up and lifestyle interventions. Results Women who have had breast cancer have an increased risk of a second primary breast cancer for at least 20 years compared to the general population. Mammographically detected local recurrences or those detected by women themselves gave better survival than those detected by clinical examination. Follow up in alternative settings to the specialist clinic is acceptable to women but trials are underpowered for survival. Conclusions Long term support, surveillance mammography and fast access to medical treatment at point of need may be better than hospital based surveillance limited to five years but further large, randomised controlled trials are needed

A framework for selecting deep learning hyper-parameters

Recent research has found that deep learning architectures show significant improvements over traditional shallow algorithms when mining high dimensional datasets. When the choice of algorithm employed, hyper-parameter setting, number of hidden layers and nodes within a layer are combined, the identification of an optimal configuration can be a lengthy process. Our work provides a framework for building deep learning architectures via a stepwise approach, together with an evaluation methodology to quickly identify poorly performing architectural configurations. Using a dataset with high dimensionality, we illustrate how different architectures perform and how one algorithm configuration can provide input for fine-tuning more complex models

Facing the urgency of therapies for progressive MS — a Progressive MS Alliance proposal

Therapies for infiltrative inflammation in multiple sclerosis (MS) have advanced greatly, but neurodegeneration and compartmentalized inflammation remain virtually untargeted as in other diseases of the nervous system. Consequently, many therapies are available for the relapsing–remitting form of MS, but the progressive forms remain essentially untreated. The objective of the International Progressive MS Alliance is to expedite the development of effective therapies for progressive MS through new initiatives that foster innovative thinking and concrete advancements. Based on these principles, the Alliance is developing a new funding programme that will focus on experimental medicine trials. Here, we discuss the reasons behind the focus on experimental medicine trials, the strengths and weaknesses of these approaches and of the programme, and why we hope to advance therapies while improving the understanding of progression in MS. We are soliciting public and academic feedback, which will help shape the programme and future strategies of the Alliance

A Comparison of Red Fluorescent Proteins to Model DNA Vaccine Expression by Whole Animal In Vivo Imaging

DNA vaccines can be manufactured cheaply, easily and rapidly and have performed well in pre-clinical animal studies. However, clinical trials have so far been disappointing, failing to evoke a strong immune response, possibly due to poor antigen expression. To improve antigen expression, improved technology to monitor DNA vaccine transfection efficiency is required. In the current study, we compared plasmid encoded tdTomato, mCherry, Katushka, tdKatushka2 and luciferase as reporter proteins for whole animal in vivo imaging. The intramuscular, subcutaneous and tattooing routes were compared and electroporation was used to enhance expression. We observed that overall, fluorescent proteins were not a good tool to assess expression from DNA plasmids, with a highly heterogeneous response between animals. Of the proteins used, intramuscular delivery of DNA encoding either tdTomato or luciferase gave the clearest signal, with some Katushka and tdKatushka2 signal observed. Subcutaneous delivery was weakly visible and nothing was observed following DNA tattooing. DNA encoding haemagglutinin was used to determine whether immune responses mirrored visible expression levels. A protective immune response against H1N1 influenza was induced by all routes, even after a single dose of DNA, though qualitative differences were observed, with tattooing leading to high antibody responses and subcutaneous DNA leading to high CD8 responses. We conclude that of the reporter proteins used, expression from DNA plasmids can best be assessed using tdTomato or luciferase. But, the disconnect between visible expression level and immunogenicity suggests that in vivo whole animal imaging of fluorescent proteins has limited utility for predicting DNA vaccine efficacy

Genetic, environmental and stochastic factors in monozygotic twin discordance with a focus on epigenetic differences

PMCID: PMC3566971This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited