Medical AI and Simulation

Medical Innovation Through Technology

RISC Software GmbH utilizes AI and simulation to elevate healthcare to a new level. Our technologies improve image processing, assist in diagnostics, and enable the development of personalized treatment approaches. Through AI-powered solutions, we enhance healthcare quality, optimize processes, and promote knowledge transfer for sustainable and safe medicine. Our research in AI and simulation increases patient safety through optimal diagnosis and surgical preparation and saves lives through early detection of emerging complications.

Simulations for Patient-Oriented Medicine

Virtual patient models allow the simulation of individual treatment courses and the early identification of potential risks. These personalized approaches help to increase safety and efficiency in patient care. Simulations also offer the opportunity to test and optimize treatment options before they are applied in practice.

Partnership Between Research and Practice

In collaboration with leading clinics and research institutions, we develop solutions that are scientifically grounded and practically viable. Our technologies have already been successfully deployed in predicting complications, in surgical training platforms, and in image segmentation. The close integration into medical practice ensures that our solutions provide tangible added value.

Shaping Medical Excellence

Learn how our technologies can shape the future of medicine. Contact RISC Software GmbH to shape the healthcare of tomorrow.

Reference Projects

HEART: Precise fluid determination through ECG signal analysis and AI

The project HEART is researching a non-invasive method for monitoring the body's fluid requirements using ECG signals. AI-supported analyses of large amounts of data support precision medicine and offer patients considerable advantages.

QML4Med: Quantum computing meets machine learning in medicine

The research project QML4Med aims to explore the potential of the promising fusion of Quantum Computing and Machine Learning in the medical context.

vizARd – Visual Augmented Reality Assistant for Spatial Mapping

Augmented reality to support preoperative planning

Research project AIMS

The aim of AIMS is to develop and validate an early warning system using artificial intelligence to warn of deteriorating conditions on the hospital ward before they occur.

SEE-KID – Software Engineering Environment for Knowledge-based Interactive Eye Motility Diagnostics

The SEE-KID / CEVD research initiative has been working on the computer-aided simulation of eye malpositions and their surgical correction for more than 20 years.