Development and Validation of a Multivariable Prediction Model for the Occurrence of Delirium in Hospitalized Gerontopsychiatry and Internal Medicine Patients. - Diether Kramer; Sai Veeranki; Dieter Hayn; Franz Quehenberger; Werner Leodolter; Christian Jagsch; Günter Schreier 001 (eHealth, 2017)

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)

EHR Text Categorization for Enhanced Patient-Based Document Navigation. - Markus Kreuzthaler; Bastian Pfeifer; José Antonio Vera Ramos; Diether Kramer; Victor Grogger; Sylvia Bredenfeldt; Markus Pedevilla; Peter Krisper; Stefan Schulz 001 (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)

Problem List Clustering for Improved Patient-Based Disease Perception. - Markus Kreuzthaler; Bastian Pfeifer; José Antonio Vera Ramos; Diether Kramer; Victor Grogger; Sylvia Bredenfeldt; Markus Pedevilla; Peter Krisper; Stefan Schulz 001 (ICHI Workshops, 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)

Predictive analytics for data driven decision support in health and care. - Dieter Hayn; Sai Veeranki; Martin Kropf; Alphons Eggerth; Karl Kreiner; Diether Kramer; Günter Schreier 001 (it Inf. Technol., 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)

EHR problem list clustering for improved topic-space navigation. - Markus Kreuzthaler; Bastian Pfeifer; José Antonio Vera Ramos; Diether Kramer; Victor Grogger; Sylvia Bredenfeldt; Markus Pedevilla; Peter Krisper; Stefan Schulz 001 (BMC Medical Informatics Decis. Mak., 2019)

A novel hybrid modeling approach for the evaluation of integrated care and economic outcome in heart failure treatment. - Alexander Lassnig; Theresa Rienmüller; Diether Kramer; Werner Leodolter; Christian Baumgartner; Joerg Schroettner (BMC Medical Informatics Decis. Mak., 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)

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)

A Comparative Study: Classification Vs. Matrix Factorization for Therapeutics Recommendation. - Seda Polat Erdeniz; Michael Schrempf; Diether Kramer; Alexander Felfernig (ISMIS, 2022)

Computational Evaluation of Model-Agnostic Explainable AI Using Local Feature Importance in Healthcare. - Seda Polat Erdeniz; Michael Schrempf; Diether Kramer; Peter P. Rainer; Alexander Felfernig; Thi Ngoc Trang Tran; Tamim Burgstaller; Sebastian Lubos (AIME, 2023)

Employing Nudge Theory and Persuasive Principles with Explainable AI in Clinical Decision Support. - Seda Polat Erdeniz; Thi Ngoc Trang Tran; Alexander Felfernig; Sebastian Lubos; Michael Schrempf; Diether Kramer; Peter P. Rainer (BIBM, 2023)

Machine Learning Based Risk Prediction for Major Adverse Cardiovascular Events for ELGA-Authorized Clinics. - Seda Polat Erdeniz; Diether Kramer; Michael Schrempf; Peter P. Rainer; Alexander Felfernig; Thi Ngoc Trang Tran; Tamim Burgstaller; Sebastian Lubos (dHealth, 2023)

Frail People in LABLand: Development of an Easy-to-Use Machine Learning Model to Identify Frail People in Hospitals Based on Laboratory Data. - Julian Gutheil; Philip Stampfer; Diether Kramer; Manuel Wechselberger; Sai Pavan Kumar Veeranki; Michael Schrempf; Peter Mrak; Martina Aubel; Franz Feichtner (dHealth, 2023)

Secondary Use of Clinical Problem List Entries for Neural Network-Based Disease Code Assignment. - Markus Kreuzthaler; Bastian Pfeifer; Diether Kramer; Stefan Schulz 001 (MIE, 2023)

A Transformer-Based Model Trained on Large Scale Claims Data for Prediction of Severe COVID-19 Disease Progression. - Manuel Lentzen; Thomas Linden; Sai Veeranki; Sumit Madan; Diether Kramer; Werner Leodolter; Holger Fröhlich (IEEE J. Biomed. Health Informatics, 2023)

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)