The University Hospital Essen, in northwestern Germany, is one such organization taking machine learning from the bits to the bedside using Nvidia technology and AI to build smart hospitals of the future.
Jens Kleesiek and Felix Nensa, professors at the School of Medicine of the University of Duisburg Essen, are part of a four-person team leading the research groups that established the Institute for Artificial Intelligence in Medicine (IKIM). The technology developed by IKIM is integrated with the IT infrastructure of University Hospital Essen.
IKIM hosts a data annotation lab, overseen by a team of board-certified radiologists, that accelerates the labeling of anatomic structures in medical images using MONAI, an open-source, PyTorch-based framework for building, training, labeling and deploying AI models for healthcare imaging.
IKIM researchers also use self-supervised learning to pretrain AI models that generate high-quality labels for the hospital’s CT scans, MRIs and more. Additionally, the IKIM team has developed a smart hospital information platform, or SHIP, an AI-based central healthcare data integration platform and deployment engine. The platform is used by researchers and clinicians to conduct real-time analysis of the slew of data in university hospitals, including medical imaging, radiology reports, clinic notes and patient interviews.
SHIP can, for example, flag an abnormality on a radiology report and notify physicians via real-time push notifications, enabling quicker diagnoses and treatments for patients. The AI can also pinpoint data-driven associations between healthcare metrics like genetic traits and patient outcomes.