Overview of Network Analysis in Systems Medicine

Systems Medicine (SM) is an interdisciplinary research paradigm, that heavily relieson complex systems theory, and emphasizes on the studies the human body in termsof systems and the interactions among them, incorporating biochemical,physiological, and environment interactions. The article presents developments in SMresearch, focusing specifically on the network analysis approaches. Network analysisis fundamental for the study of interactions among systems at different levels withinthe human body. The background knowledge is established: the basic concepts ofnodes and edges, and network metrics as well as existing computational tools aredescribed. Different applications in health research are discussed, includingdescriptive and predictive approaches. The use of network analysis in temporal dataand data coming from digital health technologies is further highlighted. Finally, thecurrent challenges are discussed and the foreseen development

Towards Explainable and Trustworthy AI for Decision Support in Medicine: An Overview of Methods and Good Practices

Artificial Intelligence (AI) is defined as intelligence exhibited by machines, such as electronic computers. It can involve reasoning, problem solving, learning and knowledge representation, which are mostly in focus in the medical domain. Other forms of intelligence, including autonomous behavior, are also parts of AI. Data driven methods for decision support have been employed in the medical domain for some time. Machine learning (ML) is used for a wide range of complex tasks across many sectors of the industry. However, a broader spectrum of AI, including deep learning (DL) as well as autonomous agents, have been recently gaining more focus and have risen expectation for solving numerous problems in the medical domain. A barrier towards AI adoption, or rather a concern, is trust in AI, which is often hindered by issues like lack of understanding of a black-box model function, or lack of credibility related to reporting of results. Explainability and interpretability are prerequisites for the development of AI-based systems that are lawful, ethical and robust. In this respect, this paper presents an overview of concepts, best practices, and success stories, and opens the discussion for multidisciplinary work towards establishing trustworthy AI

Vectors and drivers of connected health in Europe: a foundation for integrated care

Coordinated, integrated care requires connected “inputs, delivery, management and organization of services related to diagnosis, treatment, care, rehabilitation and health promotion” (Grone & Barbero, 2002). Connected health (CH) offers a key building block as a “paradigm shift, looking after the individual and community health in a process that speaks to the health journey of the person, through the entire lifespan, leveraging a variety of technologies to do so” (ENJECT, 2016). However, CH is failing to reach its full potential – and therefore failing in its contribution to the realization of integrated care

Leveraging Interdisciplinary Education Toward Securing the Future of Connected Health Research in Europe: Qualitative Study

Background: Connected health (CH) technologies have resulted in a paradigm shift, moving health care steadily toward a more patient-centered delivery approach. CH requires a broad range of disciplinary expertise from across the spectrum to work in a cohesive and productive way. Building this interdisciplinary relationship at an earlier stage of career development may nurture and accelerate the CH developments and innovations required for future health care. Objective: This study aimed to explore the perceptions of interdisciplinary CH researchers regarding the design and delivery of an interdisciplinary education (IDE) module for disciplines currently engaged in CH research (engineers, computer scientists, health care practitioners, and policy makers). This study also investigated whether this module should be delivered as a taught component of an undergraduate, master’s, or doctoral program to facilitate the development of interdisciplinary learning. Methods: A qualitative, cross-institutional, multistage research approach was adopted, which involved a background study of fundamental concepts, individual interviews with CH researchers in Greece (n=9), and two structured group feedback sessions with CH researchers in Ireland (n=10/16). Thematic analysis was used to identify the themes emerging from the interviews and structured group feedback sessions. Results: A total of two sets of findings emerged from the data. In the first instance, challenges to interdisciplinary work were identified, including communication challenges, divergent awareness of state-of-the-art CH technologies across disciplines, and cultural resistance to interdisciplinarity. The second set of findings were related to the design for interdisciplinarity. In this regard, the need to link research and education with real-world practice emerged as a key design concern. Positioning within the program context was also considered to be important with a need to balance early intervention to embed integration with later repeat interventions that maximize opportunities to share skills and experiences. Conclusions: The authors raise and address challenges to interdisciplinary program design for CH based on an abductive approach combining interdisciplinary and interprofessional education literature and the collection of qualitative data. This recipe approach for interdisciplinary design offers guidelines for policy makers, educators, and innovators in the CH space. Gaining insight from CH researchers regarding the development of an IDE module has offered the designers a novel insight regarding the curriculum, timing, delivery, and potential challenges that may be encountered

PATHway: decision support in exercise programmes for cardiac rehabilitation

Rehabilitation is important for patients with cardiovascular diseases (CVD) to improve health outcomes and quality of life. However, adherence to current exercise programmes in cardiac rehabilitation is limited. We present the design and development of a Decision Support System (DSS) for telerehabilitation, aiming to enhance exercise programmes for CVD patients through ensuring their safety, personalising the programme according to their needs and performance, and motivating them toward meeting their physical activity goals. The DSS processes data originated from a Microsoft Kinect camera, a blood pressure monitor, a heart rate sensor and questionnaires, in order to generate a highly individualised exercise programme and improve patient adherence. Initial results within the EU-funded PATHway project show the potential of our approach

An Interdisciplinary 4th Level Education Model:Connected Health

[EN] This paper responds to the need for interdisciplinary approaches to fourth level education that better reflect the complexity of the world in which we work and conduct research. We discuss this need in technology-enabled healthcare, Connected Health. We propose a model for fourth level interdisciplinary education and discuss its trial application in two European structured PhD programmes in the Connected Health research arena. We suggest broader learning objectives for the emerging fourth level graduate, methods for incorporating multiple disciplinary inputs and perspectives into deep disciplinary PhD training, intersectoral approaches to ensure employability and impact, and innovative training methods and structures to facilitate interdisciplinary and intersectoral learning. We give some examples of innovative training modules used within the pilot programmes. Finally we discuss six core elements of a truly interdisciplinary programme at fourth level - exposure to different environments, joint supervision, a genuine role for the non academic sector, career development training and planning, the development of a sustainable network beyond the life of the programme, and data openess.Mountford, N.; Kessie, T.; Watts, G.; Fernandez Luque, L.; Chouvarda, I.; Cusack, T. (2017). An Interdisciplinary 4th Level Education Model:Connected Health. En Proceedings of the 3rd International Conference on Higher Education Advances. Editorial Universitat Politècnica de València. 956-964. https://doi.org/10.4995/HEAD17.2017.5485OCS95696

Clinical validation of an algorithm for rapid and accurate automated segmentation of intracoronary optical coherence tomography images

Objectives: The analysis of intracoronary optical coherence tomography (OCT) images is based on manual identification of the lumen contours and relevant structures. However, manual image segmentation is a cumbersome and time-consuming process, subject to significant intra- and inter-observer variability. This study aims to present and validate a fully-automated method for segmentation of intracoronary OCT images. Methods: We studied 20 coronary arteries (mean length = 39.7 ± 10.0 mm) from 20 patients who underwent a clinically-indicated cardiac catheterization. The OCT images (n = 1812) were segmented manually, as well as with a fully-automated approach. A semi-automated variation of the fully-automated algorithm was also applied. Using certain lumen size and lumen shape characteristics, the fully- and semi-automated segmentation algorithms were validated over manual segmentation, which was considered as the gold standard. Results: Linear regression and Bland–Altman analysis demonstrated that both the fully-automated and semiautomated segmentation had a very high agreement with the manual segmentation, with the semi-automated approach being slightly more accurate than the fully-automated method. The fully-automated and semiautomated OCT segmentation reduced the analysis time by more than 97% and 86%, respectively, compared to manual segmentation. Conclusions: In the current work we validated a fully-automated OCT segmentation algorithm, as well as a semiautomated variation of it in an extensive “real-life” dataset of OCT images. The study showed that our algorithm can perform rapid and reliable segmentation of OCT images

The development and co-design of the PATHway intervention: a theory-driven eHealth platform for the self-management of cardiovascular disease.

Background Cardiovascular diseases (CVD) are a leading cause of premature death and disability and an economic burden worldwide. International guidelines recommend routine availability and delivery of all phases of cardiac rehabilitation (CR). Uptake of traditional cardiac rehabilitation remains suboptimal, as attendance at formal hospital-based CR programmes is low, with community-based CR rates and individual long-term exercise maintenance even lower. Home-based CR programs have been shown to be equally effective in clinical and health-related quality of life outcomes, and yet are not readily available. Purpose The aim of the current study was to develop the PATHway intervention (Physical Activity Towards Health) for the self-management of cardiovascular disease. Increasing physical activity in individuals with CVD was the primary behaviour. Methods The PATHway intervention was theoretically informed by the Behaviour Change Wheel (BCW) and Social Cognitive Theory (SCT). All relevant intervention functions, behaviour change techniques (BCTs) and policy categories were identified and translated into intervention content. Furthermore, a person-centred approach was adopted involving an iterative co-design process and extensive user-testing. Results Education, enablement, modelling, persuasion, training and social restructuring were selected as appropriate intervention functions. Twenty-two BCTs, linked to the 6 intervention functions and 3 policy categories were identified for inclusion and translated into PATHway intervention content. Conclusions This paper details the use of the BCW and SCT within a person-centred framework to develop an eHealth intervention for the self-management of CVD. The systematic and transparent development of the PATHway intervention will facilitate the evaluation of intervention effectiveness and future replication. The Template for Intervention Description and Replication (TIDieR) checklist was used to specify details of the intervention including the who, what, how and where of proposed intervention delivery

COPD care delivery pathways in five European Union countries: mapping and health care professionals’ perceptions

Background: COPD is among the leading causes of chronic morbidity and mortality in the European Union with an estimated annual economic burden of €25.1 billion. Various care pathways for COPD exist across Europe leading to different responses to similar problems. Determining these differences and the similarities may improve health and the functioning of health services. Objective: The aim of this study was to compare COPD patients’ care pathway in five European Union countries including England, Ireland, the Netherlands, Greece, and Germany and to explore health care professionals’ (HCPs) perceptions about the current pathways. Methods: HCPs were interviewed in two stages using a qualitative, semistructured email interview and a face-to-face semistructured interview. Results: Lack of communication among different health care providers managing COPD and comorbidities was a common feature of the studied care pathways. General practitioners/family doctors are responsible for liaising between different teams/services, except in Greece where this is done through pulmonologists. Ireland and the UK are the only countries with services for patients at home to shorten unnecessary hospital stay. HCPs emphasized lack of communication, limited resources, and poor patient engagement as issues in the current pathways. Furthermore, no specified role exists for pharmacists and informal carers. Conclusion: Service and professional integration between care settings using a unified system targeting COPD and comorbidities is a priority. Better communication between health care providers, establishing a clear role for informal carers, and enhancing patients’ engagement could optimize current care pathways resulting in a better integrated system. Keywords: COPD, comorbidities, care delivery pathway, comparative analysi