Enabling personalized perioperative risk prediction by using a machine-learning model based on preoperative data

Martin Graeßner, Bettina Jungwirth, Elke Frank, Stefan Josef Schaller, Eberhard Kochs, Kurt Ulm, Manfred Blobner, Bernhard Ulm, Armin Horst Podtschaske, Simone Maria Kagerbauer

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Fingerprint

Dive into the research topics of 'Enabling personalized perioperative risk prediction by using a machine-learning model based on preoperative data'. Together they form a unique fingerprint.

Keyphrases

Nursing and Health Professions

Engineering

Medicine and Dentistry

Pharmacology, Toxicology and Pharmaceutical Science

Chemical Engineering