Prof. Dr. Erwin Böttinger

Harry Freitas da Cruz, MBA

Research Assistant, PhD Candidate

Phone: +49 (331) 5509-1313
Email: Harry.FreitasDaCruz(at)hpi.de
Room: G2.2.16
Web: LinkedIn

Research Topics


  • da Cruz, H.F., Pfahringer, B., Martensen, T., Schneider, F., Meyer, A., Bottinger, E., Schapranow, M.-P.: Using Interpretability Approaches to Update textquotedblleftBlack-Boxtextquotedblright Clinical Prediction Models: an External Validation Study in Nephrology.Artificial Intelligence in Medicine.101982 (2020).
  • Datta, S., Schraplau, A., da Cruz, H.F., Sachs, J.P., Mayer, F., Böttinger, E.: A Machine Learning Approach for Non-Invasive Diagnosis of Metabolic Syndrome.2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE). p. 933--940. IEEE (2019).
  • Freitas da Cruz, H., Bergner, B., Konak, O., Schneider, F., Bode, P., Lempert, C., Schapranow, M.-P.: MORPHER – A Platform to Support Modeling of Outcome and Risk Prediction in Health Research.Proceedings of the 19th IEEE International Conference on Bioinformatics and Biomedicine. , Athens, Greece (2019).
  • Freitas da Cruz, H., Horschig, S., Nusshag, C., Schapranow, M.-P.: Knowledge Distillation from Machine Learning Models for Prediction of Hemodialysis Outcomes.International Journal On Advances in Life Sciences.11,33-43 (2019).
  • Freitas da Cruz, H., Schneider, F., Schapranow, M.-P.: Prediction of Acute Kidney Injury in Cardiac Surgery Patients: Interpretation using Local Interpretable Model-agnostic Explanations.Proceedings of the 12th International Conference on Biomedical Engineering Systems and Technologies. pp. 380-387. , Prague, Czech Republic (2019).
  • Konak, O., Freitas Da Cruz, H., Thiele, M., Golla, D., Schapranow, M.-P.: An Information and Communication Platform Supporting Analytics for Elderly Care.5th International Conference on Information for Ageing Well, Communication Technologies e Health (2019).
  • Freitas da Cruz, H., Pfahringer, B., Schneider, F., Meyer, A., Schapranow, M.-P.: External Validation of a “Black-Box” Clinical Predictive Model in Nephrology: Can Interpretability Methods Help Illuminate Performance Differences?Proceedings of 17th Conference on Artificial Intelligence in Medicine. pp. 191-201 (2019).
  • Freitas da Cruz, H., Horschig, S., Nusshag, C., Schapranow, M.-P.: Prediction of Patient Outcomes after Renal Replacement Therapy in Intensive Care.Proceedings of the 3rd International Conference on Informatics and Assistive Technologies for Health-Care, Medical Support and Wellbeing (2018).
  • Freitas da Cruz, H., Gebhardt, M., Becher, F., Schapranow, M.-P.: Interactive Data Exploration Supporting Elderly Care Planning.Proceedings of the 10th International Conference on eHealth, Telemedicine, and Social Medicine (2018).
  • Freitas da Cruz, H., Grasnick, B., Dinger, H., Bier, F., Meinel, C.: Early Detection of Acute Kidney Injury with Bayesian Networks.Proceedings of the 7th International Symposium on Semantic Mining in Biomedicine. pp. 29-36 (2016).
  • Dobkwicz, M., Jüttner, T., Freitas da Cruz, H., Heidtke, K., Finkenwirth, T., Kunze, S., Hänold, S., Nwankwo, I., Forgó, N., Schröder, C., Graf, N.: Implementation and Demonstration of the p-BioSPRE Metabiobank Platform.Demo at the 15th World Congress on Health and Biomedical Informatics (2015).