CarCor

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  Logo

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  Scheme of dataflow to build PreSure risk models for the population and the individua

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  High risk cardiovascular cluster part of PreSureAI

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  Prevention of right ventricular failure in intensive care using PreSure risk models

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  Heart and lungs models from computer tomography data of one Covid19 patient, input data for PreSure3D

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  PreSure3D diagram, predicting cardiac burden from patient specific images and ventilator parameters

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  Brainstorming and design process in PreSure

The problem

The additional cardiovascular burden created by Covid19 and ventilators in the Intensive Care Unit (ventilators cause an extra stress to the heart with the positive pressure needed to inflate the lungs from outside the body).

The solution

A risk model that predicts how well the heart will cope with Covid19 and the ventilators, both at population and individual levels.

Work done during the hackathon

Definition of problem and identification of solutions based on literature review, sharing and analysing exemplary datasets, and adapting existing research tools, skills, and know-how. Construction of a website, and of the embryo for the back-bone computational engine integrating three main technological components: mechanistic models of heart to expand and include lungs, image analysis tools and statistical population models.

The impact during the crisis

Better decisions in the management of cardiovascular disease during the Covid19 crisis in different levels: policy (who gets a vaccine because has higher risks); healthcare organization (who benefits the most from a ventilator); Intense care units (how to optimise ventilator parameters to reduce cardiac burden); individual citizen (how much to care about social distancing measures).

The necessities in order to continue the project

Resources to build the full risk model and cloud infrastructure, envisioning having a complete release within 3 months, and to conduct a retrospective study to validate our model predictions in one extra month. Total labour estimated in 26 man-months.

The impact after the crisis

Our risk models will also inform the adoption of better screening and therapy planning strategies to manage the extra cardiovascular burden created in Covid19 survivors. Our technology can also be adapted for predicting cardiovascular risks in other intensive care settings.

The team

An international consortium from academic, clinical and industrial sectors, involving doctors, biomedical engineers, computer scientists and healthcare designers. Expertise from the team: large data analysis, medical image analysis (CT/MRI/echo), cloud based technology, machine learning, mechanical modelling, clinical field knowledge and skills to define requirements and guide design, design skills, UX... We are ready and eager to make an impact in cardiac health through our risk models!

Built With

• computational-cardiology