The main goal of the 3rd Industrial workshop, promoted by the Portuguese Network for Mathematics in Industry and Innovation (PT-MATHS-IN), is to inspire new approaches to address the challenges faced by the health industry nowadays. Bringing together specialists from the health ecosystem and researchers from several areas, this workshop aims to discuss those challenges, to hear perspectives on the latest trends in healthcare and to identify promising opportunities where mathematics plays a significant role to improve that field.
Healthcare challenges are spread across many different areas such as precision medicine, big data and data management, wellness and prevention, or the social and ethical implications of advances in healthcare. Mathematics tools are often required do deal with these problems and are essential to derive effective solutions.
After last year's successes, achieved with the Big Data and Smart Security industrial days, this one-day event aims to keep bringing together Academy and Industry in the discussion of areas of great scientific or industrial relevance and with the highest societal impact.
Gathering industry, research community, start-ups and regulators in an out-of-the-box discussion at the historical and vibrant University of Coimbra - classified by UNESCO as World Heritage site - PT-MATHS-IN aims to help the participants to contact with new ideas and trends on this field, as well as to extend their network among industrials and researchers on this area.
The PT-MATHS-IN consortium of the thirteen main Portuguese mathematics research centres serves as an interface between the Portuguese Industry and the industrial mathematics community. PT-MATHS-IN also acts as the national representative of Portugal in the European Service Network for Mathematics in Industry and Innovation (EU-MATHS-IN).
This conference, organized by PT-MATHS-IN, is sponsored and supported by several institutions. Check out our sponsors and supporters. Contact us at email@example.com if you want to become a sponsor/supporter.
Ana Paula Rocha
CMUP and Department of Mathematics, FCUP, University of Porto
A journey into modelling and analysis of heart rate variability, as a window to the autonomic nervous system characterization, and with the aim of risk assessment. Complex/nonlinear characteristics of HRV are considered, namely long memory and volatility from a parametric point of view. This methodology allowed the design of individualized filters and obtaining clinically interpretable measures, reflecting changes in HRV dynamics related with the stress response to acute brain lesion and medical management. More recently we are also addressing the emerging field of network physiology, with the challenge to document the brain-organ crosstalk.
André Dias Pereira
Centre for Biomedical Law, Faculty of Law University of Coimbra, National Council of Ethics for Life Sciences
Healthcare and big data are key topics of scientific research and financial investment in recent years and is deemed to increase significantly.
Department of Biomedical Engineering, Eindhoven University of Technology
The success of deep learning neural networks is evident, leading to a revolution in the field. The breakthrough is enabled by the discovery of how to train a multi-layered neural net with backpropagation, by the advent of cheap GPU processing power and the availability of huge amounts of curated training data.
CBMA and Department of Mathematics, School of Sciences, University of Minho
This study aims, through patterns and trends, to develop models that allow to predict on a daily basis the number of patients that visit an hospital emergency department. Data on the number of admissions for an hospital emergency department was daily available on four consecutive years and prediction was made for the first trimester of the following year with no data. These data were analysed with a two-stage approach using linear regression and a time series statistical models. In the first step we model the trend of the time series allowing also for all the covariates available, using regression methods. In the second step we model temporal correlations still present in the residuals of the first step model, using time series techniques. Calendar, meteorological, environmental and epidemiological variables were tested as explanatory variables in the statistical model. However, all variables except calendar ones, proved to have small predictive value. This methodology allows emergency departments to manage resources in advance.
Isabel Narra Figueiredo
Department of Mathematics, FCTUC, University of Coimbra
Description of some different computer-assisted methods we have developed for the automatic interpretation of ophthalmological images and also gastroenterological images. In particular, we describe an automatic screening method for diabetic retinopathy, in use in Portuguese public hospitals, different colonic polyp detector methods, and, finally, a method towards wireless capsule endoscope localization.
Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra
Ageing research and innovative practices to support healthy living and active ageing became Demographic Changes priorities in Horizon 2020. The European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) stands on networks supported by quadruple helix-based regional ecosystems, the Reference Sites. Reference Sites show large-scale replication potential of innovative practices supporting independent living of citizens, the “blueprint for digital transformation on health and care in an ageing society” and “boosting innovation on active and healthy ageing in the digital single market”.
Ricardo Teresa Ribeiro
GoatLabs | ESTeSL - IPL
The Chest X-Ray (CXR) represents roughly 40% of all imaging procedures performed worldwide. It′s a preliminary diagnosis tool, enabling the detection of a wide range of lung and cardiovascular diseases. CXR shows great advantages, namely it′s low cost and easiness to perform, and it gathers a large amount of information regarding a patient′s health.
Department Mathematics and CMA - FCT University Nova de Lisboa
Physiological signals like ECG, blood pressure and respiration are closely related. However, it is challenging to develop algorithms that explore these relations to improve diagnostic or patient monitoring. We will present some examples: detection of life threatening arrhythmia alarms in the Intensive Care Unit, noninvasive fetal ECG and non invasive respiration monitoring.
President of EU-MATHS-IN
Healthcare - Challenges and opportunities from EU-MATHS-IN point of view
|Before May 15th
|After May 15th
|†Student registration does not include lunch.
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