Publikationen

Real-time risk prediction of delirium in hospitalised patients using machine learning: An implementation and prospective evaluation study.

Jauk S, Kramer D, Großauer B, Rienmüller S, Avian A, Berghold A, Leodolter W, Schulz | Juli 2020

Development of a Machine Learning Model Predicting an ICU Admission for Patients with Elective Surgery and Its Prospective Validation in Clinical Practice.

Jauk S, Kramer D, Stark G, Hasiba K, Leodolter W, Schulz S, Kainz J. | September 2019

An Improvised Classification Model for Predicting Delirium.

Veeranki SPK, Hayn D, Jauk S, Quehenberger F, Kramer D, Leodolter W, Schreier G. | September 2019

Information Adapted Machine Learning Models for Prediction in Clinical Workflow.

Jauk S, Kramer D, Quehenberger F, Veeranki SP, Hayn D, Schreier G, Leodolter W. | Juni 2019

On the Representation of Machine Learning Results for Delirium Prediction in a Hospital Information System in Routine Care.

Veeranki S, Hayn D, Eggerth A, Jauk S, Kramer D, Leodolter W, et al. | August 2018

Evaluating the Impact of Incorrect Diabetes Coding on the Performance of Multivariable Prediction Models.

Jauk S, Kramer D, Schulz S, Leodolter W. | Juli 2018