Background

In AI-SPRINT, the Life Sciences Department of the Barcelona Supercomputing Center (BSC) leads the medical use case on personalised healthcare with its focus on stroke risk assessment and prevention. Over 36 months, BSC will implement its COMPSs programming models and machine learning developments in this AI-SPRINT use case. It will use the edge-cloud environment as an effective framework to develop innovative and impactful clinical applications for stroke prevention, with a view to realising the benefits of incorporating wearable technology into healthcare, such as continuous data acquisition and low patient burden.

Use case ecosystem 

This use case combines the efforts of: 

  • Barcelona Supercomputer Center: Data analyst and modelling provider. High performance computing (HPC) provider - MareNostrum. Leading the use case and coordinating all phases of the study from wearable device acquisition to analysis and modelling as a specialist in complex data analytics for personalised medicine and accessibility to high computational power.
  • RITHMI: Wearable device provider with a team of IT entrepreneurs and doctors specialised in arrhythmia and cardiologists.
  • Foundation Freno al ICTUS: Non-profit organisation with the mission of overcoming the personal, family and social impacts of stroke-related illness. Managing use case study participants and committed to implementing the necessary protocols in compliance with all applicable laws and regulations on personal data protection.
  • María Alonso de Leciñana, MD, PhD: Stroke neurologist at “La Paz” University Hospital, in Madrid, serving as a medical advisor in the use case development and implementation. 

Key facts

In the European Union, stroke is the second most common cause of death and a leading cause of adult disability. In 2017, there were 1.12 million incident strokes in Europe, 9.53 million stroke survivors, 0.46 million deaths and 7.06 million disability-adjusted life years (DALYs) lost because of stroke. The number of people living with stroke is forecast to increase by 27% between 2017 and 2047 in the EU (Source: H. A. Wafa, et al, ‘Burden of Stroke in Europe’ in Stroke, vol. 15, No. 8, July 2020, available in open access journal). 
Associated costs are a significant burden in the EU. In 2017, this was estimated at €45 billion, including direct and indirect costs of care provision and productivity loss. These costs are expected to increase dramatically with growing populations and the number of elderly citizens alongside the rise in stroke events and their long-term sequelae. Studies has projected that the absolute burden of stroke is increasing and expected to continue over the next three decades with smaller portions of the population of working age. The imperative is to make greater efforts to prevent stroke and improve healthcare planning and priority setting, with a view to reducing the expected financial and logistic challenges in already strained healthcare systems. (Source: European Journal of Stroke, R. Luengo-Fernandez et al, vol. 5, issue 1, October 2019). 

Uniqueness

BSC’s use case focuses on personalised healthcare, collecting different kinds of information and combining quantitative and qualitative data. Per patient, the personalised model will gather this information, anonymously and respecting both privacy and security frameworks: 

  • Lifestyle information from questionnaires.
  • Biochemical measurements, like glucose, cholesterol, or haemoglobin, if available.
  • Heart parameters digital data, like heart rhythms, atrial fibrillations, electrocardiograms, from wearable devices.

BSC will enhance its high-performance data analytics framework in Edge-to-Cloud platforms to manage distribution and parallelism across the resources. 
AI-SPRINT will test its technology on a use case for personalised stroke risk assessment and prevention enhanced with AI models.
AI-SPRINT will focus on ensuring the protection of sensitive data and healthcare risk forecasting models. The distinctive AI-SPRINT framework makes possible the adoption of wearable and mobile devices to capture new insights on patient care powered by AI, with the smart allocation of the workload between cloud and edge. 

Business Impact

The final model will provide personalised notifications, alerts, and recommendations for stroke prevention, which is a reduced number of strokes, and a faster detection of risks of strokes.
This project, based on Artificial Intelligence in the healthcare industry, represents a unique opportunity for implementing effective healthcare applications working in real-time monitoring patients’ vital signs. Using Artificial Intelligence to help reinvigorate modern healthcare, such as:

  • Improved patient monitoring.
  • Enhanced patient care.
  • Reduced human error.
  • Better managed patient flow.

 

Potential societal or environmental impacts

The BSC personalised healthcare use case will significantly impact on well-being. It will pave the way for an effective framework based on Artificial Intelligence models helping to prevent stroke risks coupled with a lifestyle data. This is expected to benefit people aged between 40 and 80, improving and extending human lives. AI-SPRINT will therefore also contribute to the United Nation’s Sustainable Development Goals (SDG 3) on “Ensuring healthy lives and promoting well-being for all at all ages”, including increasing life expectancy and helping to save lives. 

 


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