PRECISE4Q · Project

AI-Powered Stroke Prediction and Treatment Planning for Hospitals and Insurers

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Imagine if your doctor could predict your stroke risk years in advance, and if one happened, knew exactly which treatment would work best for you personally. Right now, stroke care follows one-size-fits-all guidelines — like giving everyone the same shoe size. PRECISE4Q built computer models that combine your genetics, brain scans, lifestyle, and work situation to create a personalized plan covering everything from prevention through recovery and getting back to work. They tested these predictions against real hospital records and patient registries across 7 European countries.

By the numbers

EUR 5,978,245

EU contribution for platform development

consortium partners across the project

European countries represented in the consortium

patient life stages covered (prevention, acute treatment, rehabilitation, reintegration)

project deliverables produced

industry partners including SMEs in the consortium

The business problem

What needed solving

Stroke is a leading cause of death and long-term disability, and current treatment follows generic guidelines that don't account for individual patient differences in genetics, lifestyle, or social circumstances. Hospitals face high readmission rates, insurers struggle with unpredictable long-term costs, and rehabilitation providers deliver one-size-fits-all recovery programs with variable outcomes. There is no integrated system that tracks and optimizes a patient's journey from prevention through recovery and return to work.

The solution

What was built

The project built a Digital Stroke Patient Platform with multiple tools: a Stroke Risk Clinical Decision Support System (CDSS), a Treatment Outcomes CDSS, a personalized Rehab Programme, a Socio-Economic Planning Tool, and a deliberative dashboard (D1.8). These use deep learning, gradient boosting, and mechanistic brain models to generate personalized predictions validated against real clinical data.

Audience

Who needs this

Hospital networks and stroke units seeking to reduce readmission rates and improve outcomesHealth insurance companies needing better stroke cost prediction and risk stratificationRehabilitation centers wanting personalized post-stroke recovery programsDigital health companies building clinical decision support toolsPublic health authorities planning stroke prevention strategies

Business applications

Who can put this to work

Hospital systems and neurology clinics

enterprise

Target: Hospital networks and stroke units looking to improve patient outcomes and reduce readmission rates

If you are a hospital network dealing with inconsistent stroke outcomes and high readmission costs — this project developed a Clinical Decision Support System (Stroke Risk CDSS and Treatment Outcomes CDSS) that gives neurologists personalized treatment recommendations at each stage: prevention, acute care, rehabilitation, and reintegration. The system was validated with real clinical data from prospective studies and retrospective analyses across 7 countries with 13 consortium partners.

Health insurance and managed care

enterprise

Target: Health insurers seeking better risk stratification and cost prediction for stroke patients

If you are a health insurer struggling to predict and manage the long-term costs of stroke patients — this project built a Socio-Economic Planning Tool that models patient trajectories from acute event through rehabilitation and return to work. It integrates health registry data, electronic health records, and insurance data to forecast outcomes. The EUR 5,978,245 research effort specifically included health insurance data as a validation source.

Rehabilitation and physiotherapy services

mid-size

Target: Rehabilitation centers and digital health companies offering post-stroke recovery programs

If you are a rehabilitation provider dealing with generic recovery programs that don't account for individual patient needs — this project created a personalized Rehab Programme powered by machine learning that tailors recovery strategies based on the patient's specific condition, lifestyle, and social factors. The system covers coping strategies, well-being support, and reintegration into social life and work, validated with data from 13 partner institutions across 7 countries.

Frequently asked

Quick answers

What would it cost to implement this system in our hospital or organization?

The project received EUR 5,978,245 in EU funding to develop the platform across 13 partners. Licensing or implementation costs for the resulting tools (CDSS, Rehab Programme, Planning Tool) are not specified in the available project data. You would need to contact the consortium to discuss commercial terms.

Can this scale to a national or multi-hospital deployment?

The system was designed to handle heterogeneous big data from multiple sources — health registries, cohort studies, electronic health records, and insurance data — across 7 countries. This multi-source, multi-country validation suggests the architecture can scale, though deployment beyond the research setting would require further integration work with existing hospital IT systems.

Who owns the IP and how can we license it?

PRECISE4Q was funded as an RIA (Research and Innovation Action) under Horizon 2020. IP is typically retained by the consortium partners, with Charité - Universitätsmedizin Berlin as coordinator. Licensing arrangements would need to be negotiated directly with the relevant consortium members who developed specific components.

Does this meet healthcare regulatory requirements?

The predictive models were validated with real clinical data from prospective clinical studies and retrospective analyses. However, regulatory approval (e.g., CE marking as a medical device under MDR) for commercial use of the CDSS tools is not documented in the available project data. Any commercial deployment would likely require additional regulatory steps.

How long would integration with our existing systems take?

The project addressed data harmonization and semantic integration across heterogeneous sources including genomics, imaging, lifestyle data, and electronic health records. Based on available project data, the platform includes 28 deliverables including a deliberative dashboard (D1.8). Integration timelines would depend on your existing data infrastructure and the specific tools you want to deploy.

What kind of ongoing support or updates would be available?

The project ran from 2018 to 2022 and is now closed. Ongoing support would depend on whether consortium partners have continued development or formed spin-offs. The consortium included 2 industry partners and 2 SMEs who may offer commercial support for specific components.

Consortium

Who built it

The PRECISE4Q consortium brings together 13 partners from 7 countries (Austria, Switzerland, Germany, Estonia, Spain, Ireland, Sweden), led by Charité - Universitätsmedizin Berlin, one of Europe's largest university hospitals. The partnership is heavily research-oriented with 8 universities and 2 research organizations, complemented by just 2 industry partners (15% industry ratio) including 2 SMEs. This academic-heavy composition is typical for a clinical research project but means the path to commercial products may require additional industry partnerships for deployment, regulatory compliance, and market distribution. The multi-country setup is a strength for data diversity and validation across different healthcare systems.

CHARITE - UNIVERSITAETSMEDIZIN BERLINCoordinator · DE
EMPIRICA GESELLSCHAFT FUR KOMMUNIKATIONS UND TECHNOLOGIEFORSCHUNG MBHparticipant · DE
LINKOPINGS UNIVERSITETparticipant · SE
TARTU ULIKOOLparticipant · EE
UNIVERSITY COLLEGE DUBLIN, NATIONAL UNIVERSITY OF IRELAND, DUBLINparticipant · IE
MEDIZINISCHE UNIVERSITAT GRAZparticipant · AT
QMENTA IMAGING, SLparticipant · ES
DEUTSCHES FORSCHUNGSZENTRUM FUR KUNSTLICHE INTELLIGENZ GMBHparticipant · DE
UNIVERSIDAD DE MURCIAparticipant · ES
EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICHparticipant · CH
TECHNOLOGICAL UNIVERSITY DUBLINparticipant · IE
FUNDACIO INSTITUT GUTTMANNparticipant · ES

How to reach the team

Charité - Universitätsmedizin Berlin (Germany) — use SciTransfer's coordinator lookup service to find the right contact person

Order a report on this consortium See CHARITE - UNIVERSITAETSMEDIZIN BERLIN profile →

Next steps

Talk to the team behind this work.

Want to explore how PRECISE4Q's stroke prediction and personalized treatment tools could benefit your hospital, insurance company, or rehab center? SciTransfer can connect you directly with the research team and help evaluate fit for your specific use case.

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