Cardio Prime

Digital. Cardiology. Diagnostics.

Better information in heart diagnostics at the push of a button.

Less diagnostic uncertainty for improved patient care.



It’s our mission to provide specialized, computational-assisted, non-invasive diagnostics for small hospitals and cardiologists in order to improve patient care in early care path stages.



We aim to shorten the care path and improve patient care by providing digital cardiology diagnostics to small hospitals and cardiologists. With our tools we strive to reduce diagnostic uncertainties and allow more suitable, faster and patient-specific treatment in early care stages.


Today’s care path - The BIGGEST challenge of today’s healthcare systems.

The care path for cardiovascular patients, ranging from symptom detection to diagnosis, to therapy and disease management, is fragmented. Providing each patient with the right type of care at the right place of care is a key challenge for each healthcare system.

Patients in need of medical attention can expect to face delays at nearly every stage in the care path, from first consultation with a house doctor, to a specialist appointment, to hospital admission and finally treatment.

A lack of specialized tools in early care stages leads to diagnostic uncertainty. As a result of the multilevel structure of today’s care path and diagnostic uncertainty, it can take up to 5 month until a patient will get the right treatment.

With current examination techniques, it is estimated that the diagnosis of a heart disease is wrong in up to 20% of cases, leading to patients either being sent home with the risk of having a cardiac event, or undergoing unnecessary procedures.



We at cardioPrime aim to shorten the care path and decrease diagnostic uncertainty for improved patient care.

Our tools are non-invasive and easy-to-use. Simply log-in via a web-interface, choose between several diagnostic methods, fill in the required parameters and by the push of a button our tool will provide you relevant diagnostic information.


If you share our vision and care for right patient care, don’t hesitate to contact us.

We are looking for industrial cooperation for co-development and insurance companies to support us, as well as mentors from business and regulatory to enrich our advisory board.



Kay Brosien   Engineering

Kay Brosien


Kai Karlmann   Business Development

Kai Karlmann

Business Development

Markus Hüllebrand   Software

Markus Hüllebrand




Prof. Dr. med. Titus Kühne   Charité - Universitätsmedizin Berlin

Prof. Dr. med.
Titus Kühne

Charité - Universitätsmedizin Berlin

Prof. Dr.-Ing. Anja Hennemuth   Fraunhofer MEVIS

Prof. Dr.-Ing.
Anja Hennemuth

Fraunhofer MEVIS

PD Dr.-Ing. Leonid Goubergrits   Charité - Universitätsmedizin Berlin

PD Dr.-Ing.
Leonid Goubergrits

Charité - Universitätsmedizin Berlin



We are an interdisciplinary team of experts in cardiovascular disease diagnostics and treatment, physicists, engineers and software developers from Charité - Universitätsmedizin Berlin.


Our Team at cardioPrime has developed innovative digital health software for diagnosis to inform and improve the care path for patients with cardiovascular diseases. Our Solution enables physicians working in cardiovascular and other specialties at hospitals and specialist practices to diagnose cardiovascular conditions earlier and make even more informed care path decisions. One of our first applications is a stress test of cardiac and heart valve function without pharmaceutically or physical activity-induced stress. Our strongest partner is the Institute for Imaging Science and Computational Modelling, subdivision of the Charité - Universitätsmedizin Berlin. It aims at achieving a holistic system view on a patient's disease status and to better tailor therapies to the individual needs of a patient (precision medicine). For this purpose, medical data from different biological scales (organ, tissue, cell) and different sources (imaging, clinical information, omics) are processed and analyzed using methods of Data Science and applied in physiological-based modelling concepts. By combining Data Sciences with machinist physiologic-based modelling approaches, the institutes research makes important steps towards a new architecture of patient care in which the conventional boundaries between the fields of prevention, diagnosis and treatment planning are abolished.