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)

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)

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)