WARIFA · Project

AI-Powered Smartphone Apps That Predict Your Risk of Chronic Disease Before Symptoms Appear

healthTestedTRL 5

Imagine your phone could look at your daily habits — what you eat, how much you move, your sun exposure, your blood sugar — and tell you months in advance that you're heading toward a health problem. That's what WARIFA built: smartphone apps and web tools that use AI to spot early warning signs for skin cancer, diabetes complications, and lifestyle diseases. It's like a personal health weather forecast — not diagnosing what's wrong now, but warning you what's coming so you can change course.

By the numbers

EUR 6,000,000

EU funding for AI health prediction research

Consortium partners across the project

Countries represented in the consortium

Disease scenarios tested (skin cancer, diabetes, lifestyle risks)

Lifestyle risk factors addressed (diet, inactivity, tobacco, alcohol)

Total project deliverables produced

Industry partners in the consortium

The business problem

What needed solving

Chronic diseases like skin cancer, diabetes complications, and lifestyle-related conditions cost healthcare systems and employers billions annually — yet most interventions happen after symptoms appear, when treatment is expensive and outcomes are worse. Companies in health insurance, digital health, and occupational safety need tools that predict risk early enough for prevention to work, but building clinically validated AI from scratch takes years and massive investment.

The solution

What was built

WARIFA built an AI prediction engine integrated into a smartphone app system, a risk factor calculator, and a pilot prototype for monitoring risk factors across heterogeneous health data. The system covers 3 disease scenarios: skin cancer risk from sun exposure (with AI-based mole classification), diabetes complication prediction from lifestyle and blood sugar data, and general lifestyle risk assessment targeting 4 key risk factors.

Audience

Who needs this

Health insurance companies looking to reduce chronic disease claims through early preventionDigital health and mHealth app companies wanting clinically validated AI risk prediction modulesOccupational health providers managing sun exposure and lifestyle risks for workersCorporate wellness platform operators seeking evidence-based risk assessment toolsDiabetes management app developers needing complication prediction features

Business applications

Who can put this to work

Health Insurance & Wellness

enterprise

Target: Health insurance companies and corporate wellness providers

If you are a health insurer or corporate wellness provider dealing with rising chronic disease costs — this project developed an AI prediction engine and risk calculator that estimates individual risk for skin cancer, diabetes complications, and lifestyle diseases. Deployed as a smartphone app, it could help your members catch problems early, reducing expensive late-stage treatments. The system was built with 16 partners across 6 countries and tested across 3 disease scenarios.

Digital Health & mHealth

any

Target: Mobile health app developers and digital therapeutics companies

If you are a digital health company looking to add clinically validated risk prediction to your app — WARIFA built a working AI prediction engine with data fusion pipelines that process heterogeneous health data from smartphones. The pilot prototype handles everything from sun exposure tracking to blood sugar monitoring. With 5 industry partners already involved in development, the technology is designed for integration into existing health platforms.

Occupational Health & Safety

mid-size

Target: Occupational health service providers and employers with outdoor workers

If you are an occupational health provider managing sun exposure risk for outdoor workers — WARIFA developed a smartphone app that estimates personal risk for sun damage and skin cancer based on exposure history, skin type, and AI-based mole classification. The app educates users on protective behavior and flags when they should see a doctor, turning reactive injury claims into preventive health management.

Frequently asked

Quick answers

What would it cost to license or integrate this AI risk prediction technology?

The project was funded with EUR 6,000,000 in EU contribution as a Research and Innovation Action. Licensing terms would need to be negotiated directly with the coordinator (University Hospital of North Norway) and relevant consortium partners. As an RIA project, IP is typically held by the partners who generated it.

Can this scale to millions of users in a commercial health app?

The project built a pilot prototype handling heterogeneous data with a joint processing pipeline for data fusion and feature extraction. The AI prediction engine was integrated into a working system and demonstrated across 3 disease scenarios. Scaling to commercial volumes would require additional engineering beyond the research prototype stage.

Who owns the IP and how can we access it?

IP from this RIA-funded project is typically owned by the consortium partners who created it. The consortium includes 5 industry partners and 4 SMEs alongside universities and research centers. Contact the coordinator at University Hospital of North Norway to discuss licensing or collaboration options.

Has this been validated with real patients and clinical data?

The project ran 3 clinical scenarios: skin cancer risk prediction, diabetes complication prediction, and general lifestyle risk assessment. Deliverables include a pilot prototype tested on heterogeneous data and a demonstrated working app with data acquisition functionalities. The 16-partner consortium included 6 universities and 3 research organizations providing clinical expertise.

How long before this could be deployed in a commercial product?

The project ran from 2021 to 2025 and produced 43 deliverables including an integrated AI prediction engine and pilot prototype. The technology has been demonstrated but would need regulatory clearance (medical device certification) and commercial-grade engineering before market deployment. Based on available project data, the core AI and app components are functional but not yet market-ready.

Can this integrate with existing electronic health record systems?

The project designed a data fusion and feature extraction pipeline that processes multiple data types. The system includes designed graphical user interfaces and data acquisition functionalities demonstrated as part of the WARIFA app. Integration with specific EHR systems would require additional development work with the consortium's industry partners.

Consortium

Who built it

The WARIFA consortium brings together 16 partners from 6 countries (Spain, Finland, Ireland, Italy, Norway, Romania), coordinated by the University Hospital of North Norway — a clinical institution that grounds the project in real medical practice. The mix is balanced for health tech: 6 universities providing research depth, 3 research organizations for clinical validation, and critically 5 industry partners (31% of the consortium) including 4 SMEs. This industry presence signals commercial intent beyond pure research. The multi-country spread across Northern, Southern, and Eastern Europe means the technology was designed with diverse healthcare systems and populations in mind, which matters for any company looking to deploy across European markets.

UNIVERSITETSSYKEHUSET NORD-NORGE HFCoordinator · NO
UNIVERSITETET I TROMSOE - NORGES ARKTISKE UNIVERSITETparticipant · NO
UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIAparticipant · ES
PNO DIGITAL SRLthirdparty · IT
SERVICIO CANARIO DE LA SALUDparticipant · ES
MUNSTER TECHNOLOGICAL UNIVERSITYparticipant · IE
CONSIGLIO NAZIONALE DELLE RICERCHEparticipant · IT
PNO INNOVATION SRLparticipant · IT
UNIVERSITETET I OSLOparticipant · NO
UNIVERSIDAD REY JUAN CARLOSparticipant · ES
UNIVERSITATEA DE MEDICINA SI FARMACIE CAROL DAVILA DIN BUCURESTIparticipant · RO

How to reach the team

University Hospital of North Norway (Universitetssykehuset Nord-Norge HF) — reach out to their research partnerships or technology transfer office

Order a report on this consortium See UNIVERSITETSSYKEHUSET NORD-NORGE HF profile →

Next steps

Talk to the team behind this work.

Want to explore licensing WARIFA's AI prediction engine or risk calculator for your health product? SciTransfer can connect you directly with the right consortium partner. Contact us for a tailored introduction.

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