Explore the words cloud of the PERISCOPE project. It provides you a very rough idea of what is the project "PERISCOPE" about.
The following table provides information about the project.
Coordinator |
HEALTHPLUS.AI-IP BV
Organization address contact info |
Coordinator Country | Netherlands [NL] |
Total cost | 71˙429 € |
EC max contribution | 50˙000 € (70%) |
Programme |
1. H2020-EU.3. (PRIORITY 'Societal challenges) 2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs) 3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies) |
Code Call | H2020-SMEInst-2018-2020-1 |
Funding Scheme | SME-1 |
Starting year | 2019 |
Duration (year-month-day) | from 2019-06-01 to 2019-11-30 |
Take a look of project's partnership.
# | ||||
---|---|---|---|---|
1 | HEALTHPLUS.AI-IP BV | NL (AMSTERDAM) | coordinator | 50˙000.00 |
Some 50M people need to undergo inpatient surgery per year in Europe Yet, despite intensive research efforts, around 25% of surgical patients will experience a complicated recovery with some type of infection on their path: pneumonia, urinary tract infections, wound infections, abdominal infections and bacteremia. Of course, the risk varies depending on the patient and the procedure, but despite efforts like biomarkers, risk scores or devices for early warning/detection, and preventive methods like ‘Enhanced Recovery After Surgery’ (ERAS), the overall risk still leaves almost one in four patients to get an infection within 30-days after surgery.
If we look beyond the personal suffering of patients and relatives, the cost of an infectious complication is estimated at around €10,000 per patient. Hence, total cost in only the Netherlands alone can be calculated at up to €3.5B per year, as approximately 350,000 Dutch patients go through an infection after surgery yearly. Total EU costs are even more shocking at an estimated €125B per year.
Healthplus.ai R&D BV is currently developing an advanced machine-learning (ML) algorithm (TRL level 4) to predict post-operative infections 5 days prior to the average medical team diagnosis, currently already achieving an accuracy of 80%. Through increasing the dataset and taking on more types of data, the ultimate goal is to ultimately achieve >90% accuracy at 5 days before the infectious symptoms on average are actually detected within the patient.
In this proposal, we seek how to go beyond the proven technical feasibility and assess channels to deliver the tool in a safe, affordable and scalable way through third-party vendors with a sustainable business model and plan with the right partnerships and intensify these relationships. Also, potential legal and regulatory issues with EU expansion will be identified, investigated and suitable measures outlined.
Are you the coordinator (or a participant) of this project? Plaese send me more information about the "PERISCOPE" project.
For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.
Send me an email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.
Thanks. And then put a link of this page into your project's website.
The information about "PERISCOPE" are provided by the European Opendata Portal: CORDIS opendata.
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