Keynote speakers

Large networks of disease-disease interactions at the medical and molecular level.

ABSTRACT: Biomedicine is confronting significant challenges for the handling and analysis of large data sets, among them a particularly relevant one is the interaction between diseases, i.e. disease comorbidities. Comorbidities are an important medical and social problem that demands an interpretation of the underlying physiological causes, as a necessary step to progress in its management and control. As a first step in this direction, we have analysed two complementary data sets, one composed by a large collection of expression data (RNAseq data 72 human diseases analysed by 107 studies, including a total number of 4.267 samples, from the GREIN platform) the other one base on medical records from three different medical systems (Blumenau, Brazil; Catalonia, Spain; and Indianapolis, United States) or from previous publications (Hidalgo et al. 2009 and Jensen  et al. 2014). With this information, we have constructed two disease-disease interaction networks, one reflecting real-world medical associations and the other the similarities of the molecular profiles of patients of different diseases. Interestingly, the two networks have striking similarities in terms of their organization and characteristics. More importantly, we can show for the first time that most disease interactions have a counterpart at the molecular level. This molecular relationship can be translated into detailed molecular basis of specific disease interactions. I will discuss the implications of these results for the interpretation of diseases interactions at the level of specific genes and pathways, as well as the potential consequences for the management of disease comorbidities.

Based on the work of: Beatriz Urda-García, Jon Sanchez, Rosalba Lepore at BSC.

Simplifying interpretation and acquisition of ultrasound scans

ABSTRACT: With the increased availability of low-cost and handheld ultrasound probes, there is interest in simplifying interpretation and acquisition of ultrasound scans through deep-learning based analysis so that ultrasound can be used more widely in healthcare. However, this is not just “all about the algorithm”, and successful innovation requires inter-disciplinary thinking and collaborations.

In this talk I will overview progress in this area drawing on examples of my laboratory’s  experiences of working with partners on multi-modal ultrasound imaging, and building assistive algorithms and devices for pregnancy health assessment in  high-income and low-and-middle-income country settings. Emerging topics in this area will also be discussed.

Digital Health Technology – leveraging real-world insights in mobility

ABSTRACT: Mobility is important – the last year has brought this into sharp focus.  Mobility is not only a target for intervention, subtle features of mobility (such as how fast someone walks and how variable their steps are) provide us with a window into the brain and body and an indicator of health.  As a clinician, mobility has been my focus. In particular, how do we keep people with neurodegenerative disease such as Parkinson’s – mobile and safe?  This propelled me towards the scientific study of gait – a key feature of mobility.  The last 10 years have seen a revolution in digital technology (such as wearables and mobile devices) advancing the study of mobility. Implementing technology in the real-world allows further insights into health previously unobtainable and a ‘living-lab’ approach to study and treat mobility loss.  Continuous monitoring captures the challenges of mobility that play out in real-time at the intersection between personal, contextual and environmental demands and bring a personalized focus to healthcare.  However, large scale implementation of real-world mobility assessment and treatment, although promising, remains tantalizingly out of reach. This talk will focus on experiences and insights using digital technology to quantify mobility in Parkinson’s disease, explore challenges to extract meaningful insights from continuous real-world mobility data, and highlight future possibilities. Throughout I will draw on my own experience using digital technology and leverage insights from the work of the Mobilise-D consortium (https://www.mobilise-d.eu/), a large international effort to translate real-world mobility assessment to research and healthcare.

Leveraging Electronic Health Records for Precision Health

ABSTRACT: Biomedical data science has experienced an explosion of new data over the past decade. Abundant genetic and genomic data are increasingly available in large, diverse data sets due to the maturation of modern molecular technologies. Along with these molecular data, dense, rich phenotypic data are also available on comprehensive clinical data sets from health care provider organizations, clinical trials, population health registries, and epidemiologic studies. The methods and approaches for interrogating these large genetic/genomic and clinical data sets continue to evolve rapidly, as our understanding of the questions and challenges continues to develop. Through applying bioinformatics, statistics, and machine learning approaches to the rich phenotypic data of the EHR, these data can be mined to identify new and interesting patterns of disease expression and relationships.  We have been exploring various translational bioinformatics technologies for evaluating the phenomic landscape to improve our understanding of complex traits.  These techniques show great promise for the future of precision medicine and precision health.

Soft, Wearable Systems with Integrated Microfluidics and Biosensors for Remote Health Monitoring

ABSTRACT: Soft bio-electronics and microfluidics, enabled by recent advances in materials science and mechanics, can be designed with physical properties that approach the mechanical properties of human skin. These systems are referred to as epidermal electronics and epifluidics by virtue of their stretchable form factors and soft mechanics compared to conventional packaged electronics and sensors. Here, we present an overview of recent advances in novel materials, mechanics, and designs for emerging classes of fully-integrated epidermal electronics and soft microfluidic systems. These devices incorporate arrays of sensors, microfluidic channels and biochemical assays, configured in ultrathin, stretchable formats for continuous monitoring of electro-chemical signals and biophysical metrics. Quantitative analyses of strain distribution and circuit performances under mechanical stress highlight the utility of these wearable systems in clinical and home environments. We will conclude with representative examples of these wearable systems, which have entered the commercialization phase of deployment.

Improving Consideration of Social and Cognitive Behaviors in Advancing Informatics Technologies for Health Care

ABSTRACT: The modern landscape is being shaped by complex converging forces that will cause shifts in how we deliver and use health care. As we embrace inevitable technological advances, social and cognitive factors will need to be a major part of the discussion, with a focus on the users of the technical innovations. Current efforts to advance this goal have already started. However, there is still a disparity between the users’ knowledge and expectations of the technical systems being introduced and their lay beliefs, limited mental models of the technology, and their cognitive representations of illness and disease. Social cognition is predicated upon the belief that both patients and clinicians are predisposed to see the world in individualized ways that shape their behavior and decision-making. These factors are too often misunderstood or ignored in the design and evaluation of engineering systems. A major challenge for health informatics in the future will be to generate evidence-based information about how people process medical and health-related information, with and without supporting technologies. There will be a much greater need for collaborative efforts among scientists (biomedical, cognitive, and social), practitioners, and engineers, as they design and implement systems, if we are to offer technologies that are embraced and thereby reshape the future of our healthcare for a better quality of life. I will address some of these issues with examples from cognitive informatics studies, which influence users’ behavior as they interact with health care technology.

Wearable “SUPER-MINDS” for the Precision Control of CVDs and COVIDs

ABSTRACT: The cardiovascular diseases (CVDs) and coronavirus diseases (COVIDs) are the most current pressing health challenges globally today. This talk will attempt to address the grand challenges through the paradigm shift to Health Informatics and discuss the convergence approach to integrate technologies across multiple scales in the biological hierarchy from molecular, cell, organ to system for diseases prevention. The presentation will focus on the development of wearable ‘SUPER-MINDS’ technologies and their integrations with unobtrusive sensing, biomarker detection, biomedical imaging and machine learning for the early prediction of acute CVDs. Potential applications in the fast response and precise control of COVID-19 will also be discussed. Using the atherosclerotic plaque assessment as an example, this talk will illustrate that the health convergence approach should allow the practice of 8- P’s proactive medicine that is predictive, preventive, precise, pervasive, personalized, participatory, preemptive, and patient-centralized.