The power of Artificial Intelligence

Artificial Intelligence to improve cancer care

We are creating an interoperable and distributed EU ecosystem for action on Pediatric Cancer that will provide top qualityevidence-based AI services to accelerate an early diagnosis, prognosis, treatment and care of children with cancer

Our Proposition

Every healthcare interaction in the cancer patient journey generates precious,  highly sensitive data. The main challenges in the digitization of pediatric cancer data are privacy, data robustness and a lack of interoperability and collaborative approaches. Additionally, data sharing has traditionally been held back by the economic cost of processing and the diversity in national regulations and constraints on handling sensitive data.

We shift the focus to how successful AI interventions can effectively unlock hidden insights from all this data without losing sight of the fundamental ethical, personal and legal rights that must be put under the spotlight.

Shining a light on Childhood Cancer

Co-designing a new EU-wide methodology that will support specific AI-based interventions for Childhood Cancer in compliance with the highest medical and safety standards to ensure their clinical usability 

From AI theory to clinical practice

A set of clinical use cases that endorse trustworthy and reliable AI and address the inherent challenges in data homogenization, interoperability, processing and federation

A patient-centric approach

Advocating for strategic policy contributions that expand on existing standards and guidelines to boost the adoption of AI techniques in healthcare to serve and protect patients and caregivers’ needs and rights

Strengthening our community

By incorporating the outlook and knowledge from pediatric oncologists, AI practitioners, the healthcare industry and standardization bodies to create a solid foundation for accessing and sharing health data

Our work plan

Helping children and adolescent with cancer through AI: benchmarking algorithms for early detection, diagnosis, treatment, risk scores and patient stratification to build a framework that can improve the stand of care and address unmet needs for patients, caregivers and clinicians