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)

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)