AIQNET
The goal is to develop a digital ecosystem that enables the use of clinical and medical data across sectors and in compliance with data protection laws. To this end, the procurement, structuring and analysis of medical data will be largely automated with the help of artificial intelligence (AI). The project thus solves three central problems that inhibit progress in medical technology and healthcare as a whole:
AIQNET creates holistic access to medical and clinical data needed by researchers, doctors, industry for research purposes and to comply with legal requirements (compliance), and which is currently distributed across many different systems.
AIQNET creates the conditions for the legal usability of the data, which is often not given due to the lack of patient participation and non-transparent processes.
AIQNET creates a platform for the broad use of health data for research and evidence-based medicine to enable a high level of interoperability of IT systems and the availability of structured data for optimal patient treatment.
AIQNET is an open system that creates value for all stakeholders through its compatibility and neutrality.
Our vision: An ecosystem with 100 applications and installations as well as 1000 connected clinics within 5 years
The consortium has many universities and industry partners. Charité being one among them has the use case ‘Artificial intelligence for automated collection, structuring and evaluation of medical data, especially to increase evidence in complex spinal surgeries’. Patients are evaluated using pre- and post-operative X-rays and their PROMs for spinal surgery treatment prognosis using Artificial Intelligence to statistically measure their improvement.
CEI supports the project AIQNET and the consortium members on the needs of medical terminologies and interoperability standards to structure and store the relevant research data. LOINC, HL7 FHIR are being used in the projects to make the data interoperable and readily available among the consortium for further research optimizations.