Perioperative infection prediction

Project description

Machine-learning algorithm for early prediction of postoperative infections

Around 25 % of surgical patients in Europe experience some type of postoperative complication in the form of an infection. Dutch company Healthplus.ai is developing an advanced machine-learning algorithm to predict postoperative infections five days before the medical team diagnosis, achieving an accuracy of 80 %. The EU-funded PERISCOPE project aims to increase the data set and achieve > 90 % accuracy at five days before the onset of potential infection symptoms in the patient. The project is also focussing on a sustainable business model and plan, partnerships as well as legal and regulatory issues.

Fields of science

• medical and health sciences › clinical medicine › pneumology
• medical and health sciences › clinical medicine › surgery
• medical and health sciences › clinical medicine › urology
• medical and health sciences › health sciences › infectious diseases
• social sciences › economics and business › economics › sustainable economy

Programme(s)

• H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs Main Programme
• H2020-EU.3. - PRIORITY 'Societal challenges
• H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies

Topic(s)

• EIC-SMEInst-2018-2020 - SME instrument

Call for proposal

H2020-EIC-SMEInst-2018-2020

See other projects for this call

Sub call

H2020-SMEInst-2018-2020-1

Funding Scheme

SME-1 - SME instrument phase 1

Coordinator

HEALTHPLUS.AI-IP BV

Net EU contribution

€ 50 000,00

Address

Singel 542
1017 AZ Amsterdam
Netherlands

Region

West-Nederland › Noord-Holland › Groot-Amsterdam

Activity type

Private for-profit entities (excluding Higher or Secondary Education Establishments)

Links

Other funding

€ 21 429,00