With more than 15 years of experience in EU-funded and commercial projects, Lynkeus successfully carried out several innovations and impacting projects and participated in several proposals.

SIMCor (In Silico testing and validation of Cardiovascular Implantable devices, H2020, 2021 – 2023). SIMCor will develop an open, reusable, cloud-based platform for the in-silico testing, validation and regulatory approval of cardiovascular implantable devices at the service of researchers, medical device manufacturers and regulatory bodies.

EuCanImage (A European Cancer Image Platform Linked to Biological and Health Data for Next-Generation Artificial Intelligence and Precision Medicine in Oncology, H2020, 2020 – 2022). The goal of EuCanImage is to build a highly secure, federated and large-scale European cancer imaging platform, with capabilities that will greatly enhance the potential of artificial intelligence in oncology.

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KRAKEN (BroKeRage And marKet platform for pErsoNal data, H2020,  2019 – 2022). KRAKEN will deliver a trusted and secure personal data platform with state-of-the-art privacy aware analytics methods, enabling the sharing/brokerage/trading of potentially sensitive personal data under the full control of citizens (data subjects) throughout the entire data lifecycle.

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euCanSHare (An EU-Canada joint infrastructure for next-generation multi-Study Heart research, H2020, 2018 – 2022) is a joint EU-Canada project to establish a cross-border data sharing and multi-cohort cardiovascular research platform, including a web-based data access system with functionalities for increased efficiency in cardiovascular data-driven research.

MHMD (MyHealth-MyData, H2020, 2016-2019) is a blockchain-based system for health, which has exerted the function of a technological, ethical and legal sandbox for testing the feasibility, robustness and meaningfulness of a new privacy paradigm allowing to develop “trust-less trust” to facilitate data transactions between citizens, hospitals, research centres, and businesses. It introduced advanced privacy-enhancing technologies based on “bringing the algorithms to the data” with secure computation and generating synthetic data coupled with differential privacy.

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