Cleansing and Imputation of Body Mass Index Data and Its Impact on a Machine Learning Based Prediction Model. - Stefanie Jauk; Diether Kramer; Werner Leodolter (eHealth, 2018)

Effect of Nursing Assessment on Predictive Delirium Models in Hospitalised Patients. - Sai Pavan Kumar Veeranki; Dieter Hayn; Diether Kramer; Stefanie Jauk; Günter Schreier 001 (eHealth, 2018)

Evaluating the Impact of Incorrect Diabetes Coding on the Performance of Multivariable Prediction Models. - Stefanie Jauk; Diether Kramer; Stefan Schulz 001; Werner Leodolter (ICIMTH, 2018)

On the Representation of Machine Learning Results for Delirium Prediction in a Hospital Information System in Routine Care. - Sai Veeranki; Dieter Hayn; Alphons Eggerth; Stefanie Jauk; Diether Kramer; Werner Leodolter; Günter Schreier 001 (ICIMTH, 2018)

Information Adapted Machine Learning Models for Prediction in Clinical Workflow. - Stefanie Jauk; Diether Kramer; Franz Quehenberger; Sai Pavan Kumar Veeranki; Dieter Hayn; Günter Schreier 001; Werner Leodolter (dHealth, 2019)

Is Regular Re-Training of a Predictive Delirium Model Necessary After Deployment in Routine Care? - Sai Pavan Kumar Veeranki; Diether Kramer; Dieter Hayn; Stefanie Jauk; Alphons Eggerth; Franz Quehenberger; Werner Leodolter; Günter Schreier 001 (dHealth, 2019)

Development of a Machine Learning Model Predicting an ICU Admission for Patients with Elective Surgery and Its Prospective Validation in Clinical Practice. - Stefanie Jauk; Diether Kramer; Günther Stark; Karl Hasiba; Werner Leodolter; Stefan Schulz 001; Johann Kainz (MedInfo, 2019)

An Improvised Classification Model for Predicting Delirium. - Sai Pavan Kumar Veeranki; Dieter Hayn; Stefanie Jauk; Franz Quehenberger; Diether Kramer; Werner Leodolter; Günter Schreier 001 (MedInfo, 2019)

Multivariable Risk Prediction of Dysphagia in Hospitalized Patients Using Machine Learning. - Anna-Maria Lienhart; Diether Kramer; Stefanie Jauk; Markus Gugatschka; Werner Leodolter; Thomas Schlegl (dHealth, 2020)

Risk prediction of delirium in hospitalized patients using machine learning: An implementation and prospective evaluation study. - Stefanie Jauk; Diether Kramer; Birgit Großauer; Susanne Rienmüller; Alexander Avian; Andrea Berghold; Werner Leodolter; Stefan Schulz 001 (J. Am. Medical Informatics Assoc., 2020)

Machine Learning Based Risk Prediction for Major Adverse Cardiovascular Events. - Michael Schrempf; Diether Kramer; Stefanie Jauk; Sai Pavan Kumar Veeranki; Werner Leodolter; Peter P. Rainer (dHealth, 2021)

Reply to Rousseau and Tierney. - Stefanie Jauk (J. Am. Medical Informatics Assoc., 2021)

Technology Acceptance of a Machine Learning Algorithm Predicting Delirium in a Clinical Setting: a Mixed-Methods Study. - Stefanie Jauk; Diether Kramer; Alexander Avian; Andrea Berghold; Werner Leodolter; Stefan Schulz 001 (J. Medical Syst., 2021)

Correction to: Technology Acceptance of a Machine Learning Algorithm Predicting Delirium in a Clinical Setting: a Mixed-Methods Study. - Stefanie Jauk; Diether Kramer; Alexander Avian; Andrea Berghold; Werner Leodolter; Stefan Schulz 001 (J. Medical Syst., 2021)

External Validation of a Machine Learning Based Delirium Prediction Software in Clinical Routine. - Stefanie Jauk; Sai Pavan Kumar Veeranki; Diether Kramer; Stefan Högler; David Mühlecker; Erwin Eberhartl; Arthur Schueler; Christian Chvosta; Wolfgang Strasser; Reinhold Strasser; Werner Leodolter (dHealth, 2022)

Development of an Architecture to Implement Machine Learning Based Risk Prediction in Clinical Routine: A Service-Oriented Approach. - Michael Schrempf; Seda Polat Erdeniz; Diether Kramer; Stefanie Jauk; Sai Pavan Kumar Veeranki; Werner Ribitsch; Werner Leodolter; Peter P. Rainer (dHealth, 2022)

Machine Learning-Based Prediction of Malnutrition in Surgical In-Patients: A Validation Pilot Study. - Diether Kramer; Stefanie Jauk; Sai Veeranki; Michael Schrempf; Julia Traub; Eva Kugel; Anna Prisching; Sandra Domnanich; Maria Leopold; Peter Krisper; Gerald Sendlhofer (dHealth, 2024)